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Bartlett JJ, Davey CE, Johnston LA, Duan J. Recovering high-quality fiber orientation distributions from a reduced number of diffusion-weighted images using a model-driven deep learning architecture. Magn Reson Med 2024; 92:2193-2206. [PMID: 38852179 DOI: 10.1002/mrm.30187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 04/09/2024] [Accepted: 05/20/2024] [Indexed: 06/11/2024]
Abstract
PURPOSE The aim of this study was to develop a model-based deep learning architecture to accurately reconstruct fiber orientation distributions (FODs) from a reduced number of diffusion-weighted images (DWIs), facilitating accurate analysis with reduced acquisition times. METHODS Our proposed architecture, Spherical Deconvolution Network (SDNet), performed FOD reconstruction by mapping 30 DWIs to fully sampled FODs, which have been fit to 288 DWIs. SDNet included DWI-consistency blocks within the network architecture, and a fixel-classification penalty within the loss function. SDNet was trained on a subset of the Human Connectome Project, and its performance compared with FOD-Net, and multishell multitissue constrained spherical deconvolution. RESULTS SDNet achieved the strongest results with respect to angular correlation coefficient and sum of squared errors. When the impact of the fixel-classification penalty was increased, we observed an improvement in performance metrics reliant on segmenting the FODs into the correct number of fixels. CONCLUSION Inclusion of DWI-consistency blocks improved reconstruction performance, and the fixel-classification penalty term offered increased control over the angular separation of fixels in the reconstructed FODs.
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Affiliation(s)
- Joseph J Bartlett
- Department of Biomedical Engineering, Melbourne Brain Centre Imaging Unit, Graeme Clark Institute, The University of Melbourne, Parkville, Victoria, Australia
- School of Computer Science, University of Birmingham, Birmingham, UK
| | - Catherine E Davey
- Department of Biomedical Engineering, Melbourne Brain Centre Imaging Unit, Graeme Clark Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - Leigh A Johnston
- Department of Biomedical Engineering, Melbourne Brain Centre Imaging Unit, Graeme Clark Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - Jinming Duan
- School of Computer Science, University of Birmingham, Birmingham, UK
- The Alan Turing Institute, London, UK
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2
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Karan P, Edde M, Gilbert G, Barakovic M, Magon S, Descoteaux M. Characterization of the orientation dependence of magnetization transfer measures in single and crossing-fiber white matter. Magn Reson Med 2024; 92:2207-2221. [PMID: 38924176 DOI: 10.1002/mrm.30195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 04/23/2024] [Accepted: 05/25/2024] [Indexed: 06/28/2024]
Abstract
PURPOSE To fully characterize the orientation dependence of magnetization transfer (MT) and inhomogeneous MT (ihMT) measures in the whole white matter (WM), for both single-fiber and crossing-fiber voxels. METHODS A characterization method was developed using the fiber orientation obtained from diffusion MRI (dMRI) with diffusion tensor imaging (DTI) and constrained spherical deconvolution. This allowed for characterization of the orientation dependence of measures in all of WM, regardless of the number of fiber orientation in a voxel. Furthermore, the orientation dependence inside 31 different WM bundles was characterized to evaluate the homogeneity of the effect. Variation of the results within and between-subject was assessed from a 12-subject dataset. RESULTS Previous results for single-fiber voxels were reproduced and a novel characterization was produced in voxels of crossing fibers, which seems to follow trends consistent with single-fiber results. Heterogeneity of the orientation dependence across bundles was observed, but homogeneity within similar bundles was also highlighted. Differences in behavior between MT and ihMT measures, as well as the ratio and saturation versions of these, were noted. CONCLUSION Orientation dependence characterization was proven possible over the entirety of WM. The vast range of effects and subtleties of the orientation dependence on MT measures showed the need for, but also the challenges of, a correction method.
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Affiliation(s)
- Philippe Karan
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - Manon Edde
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | | | - Muhamed Barakovic
- Pharma Research and Early Development, Neuroscience and Rare Diseases Roche Innovation Center Basel, Basel, Switzerland
| | - Stefano Magon
- Pharma Research and Early Development, Neuroscience and Rare Diseases Roche Innovation Center Basel, Basel, Switzerland
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
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3
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Kanel D, Fox NA, Pine DS, Zeanah CH, Nelson CA, McLaughlin KA, Sheridan MA. Altered associations between white matter structure and psychopathology in previously institutionalized adolescents. Dev Cogn Neurosci 2024; 69:101440. [PMID: 39241456 PMCID: PMC11405635 DOI: 10.1016/j.dcn.2024.101440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 07/24/2024] [Accepted: 08/24/2024] [Indexed: 09/09/2024] Open
Abstract
Previously institutionalized adolescents show increased risk for psychopathology, though placement into high-quality foster care can partially mitigate this risk. White matter (WM) structure is associated with early institutional rearing and psychopathology in youth. Here we investigate associations between WM structure and psychopathology in previously institutionalized youth. Adolescent psychopathology data were collected using the MacArthur Health and Behavior Questionnaire. Participants underwent diffusion MRI, and data were processed using fixel-based analyses. General linear models investigated interactions between institutionalization groups and psychopathology on fixel metrics. Supplementary analyses also examined the main effects of psychopathology and institutionalization group on fixel metrics. Ever-Institutionalized children included 41 randomized to foster care (Mage=16.6), and 40 to care-as-usual (Mage=16.7)). In addition, 33 participants without a history of institutionalization were included as a reference group (Mage=16.9). Ever-Institutionalized adolescents displayed altered general psychopathology-fixel associations within the cerebellar peduncles, inferior longitudinal fasciculi, corticospinal tract, and corpus callosum, and altered externalizing-fixel associations within the cingulum and fornix. Our findings indicate brain-behavior associations reported in the literature may not be generalizable to all populations. Previously institutionalized youth may develop differential brain development, which in turn leads to altered neural correlates of psychopathology that are still apparent in adolescence.
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Affiliation(s)
- Dana Kanel
- Department of Human Development, University of Maryland, United States; Emotion and Development Branch, National Institute of Mental Health, United States.
| | - Nathan A Fox
- Department of Human Development, University of Maryland, United States
| | - Daniel S Pine
- Emotion and Development Branch, National Institute of Mental Health, United States
| | - Charles H Zeanah
- Department of Psychiatry and Behavioral Sciences, Tulane University School of Medicine, United States
| | - Charles A Nelson
- Division of Developmental Medicine, Boston Children's Hospital, United States; Department of Pediatrics, Harvard Medical School, United States; Harvard Graduate School of Education, United States
| | | | - Margaret A Sheridan
- Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, United States
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4
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Hu Q, Li M, Li M, Zeng Q, Yu J, Wang X, Xia Z, Xie L, Zhang J, Huang J, Liang J, Chen G, Wu X, Feng Y. Preoperative diffusion tensor imaging: Fiber-trajectory-distribution-based tractography to identify facial nerve in vestibular schwannoma. Magn Reson Med 2024; 92:1755-1767. [PMID: 38860542 DOI: 10.1002/mrm.30160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 04/11/2024] [Accepted: 05/04/2024] [Indexed: 06/12/2024]
Abstract
PURPOSE Tractography of the facial nerve based on diffusion MRI is instrumental before surgery for the resection of vestibular schwannoma, but no excellent methods usable for the suppression of motion and image noise have been proposed. The aim of this study was to effectively suppress noise and provide accurate facial nerve reconstruction by extend a fiber trajectory distribution function based on the fourth-order streamline differential equations. METHODS Preoperative MRI from 33 patients with vestibular schwannoma who underwent surgical resection were utilized in this study. First, T1WI and T2WI were used to obtain mask images and regions of interest. Second, probabilistic tractography was employed to obtain the fibers representing the approximate facial nerve pathway, and these fibers were subsequently translated into orientation information for each voxel. Last, the voxel orientation information and the peaks of the fiber orientation distribution were combined to generate a fiber trajectory distribution function, which was used to parameterize the anatomical information. The parameters were determined by minimizing the cost between the trajectory of fibers and the estimated directions. RESULTS Qualitative and visual analyses were used to compare facial nerve reconstruction with intraoperative recordings. Compared with other methods (SD_Stream, iFOD1, iFOD2, unscented Kalman filter, parallel transport tractography), the fiber-trajectory-distribution-based tractography provided the most accurate facial nerve reconstructions. CONCLUSION The fiber-trajectory-distribution-based tractography can effectively suppress the effect of noise. It is a more valuable aid for surgeons before vestibular schwannoma resection, which may ultimately improve the postsurgical patient's outcome.
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Affiliation(s)
- Qiming Hu
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
- Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou, China
| | - Mingchu Li
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, China
| | - Mengjun Li
- Department of Neurosurgery, Xiangya Hospital Central South University, Changsha, China
| | - Qingrun Zeng
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
- Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou, China
| | - Jiangli Yu
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
- Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou, China
| | - Xu Wang
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, China
| | - Ze Xia
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
- Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou, China
| | - Lei Xie
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
- Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou, China
| | - Jiawei Zhang
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
- Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou, China
| | - Jiahao Huang
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
- Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou, China
| | - Jiantao Liang
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, China
| | - Ge Chen
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, China
| | - Xiaolong Wu
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, China
| | - Yuanjing Feng
- Institute of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
- Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou, China
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Azilinon M, Wang HE, Makhalova J, Zaaraoui W, Ranjeva JP, Bartolomei F, Guye M, Jirsa V. Brain sodium MRI-derived priors support the estimation of epileptogenic zones using personalized model-based methods in epilepsy. Netw Neurosci 2024; 8:673-696. [PMID: 39355432 PMCID: PMC11340996 DOI: 10.1162/netn_a_00371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Accepted: 03/06/2024] [Indexed: 10/03/2024] Open
Abstract
Patients presenting with drug-resistant epilepsy are eligible for surgery aiming to remove the regions involved in the production of seizure activities, the so-called epileptogenic zone network (EZN). Thus the accurate estimation of the EZN is crucial. Data-driven, personalized virtual brain models derived from patient-specific anatomical and functional data are used in Virtual Epileptic Patient (VEP) to estimate the EZN via optimization methods from Bayesian inference. The Bayesian inference approach used in previous VEP integrates priors, based on the features of stereotactic-electroencephalography (SEEG) seizures' recordings. Here, we propose new priors, based on quantitative 23Na-MRI. The 23Na-MRI data were acquired at 7T and provided several features characterizing the sodium signal decay. The hypothesis is that the sodium features are biomarkers of neuronal excitability related to the EZN and will add additional information to VEP estimation. In this paper, we first proposed the mapping from 23Na-MRI features to predict the EZN via a machine learning approach. Then, we exploited these predictions as priors in the VEP pipeline. The statistical results demonstrated that compared with the results from current VEP, the result from VEP based on 23Na-MRI prior has better balanced accuracy, and the similar weighted harmonic mean of the precision and recall.
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Affiliation(s)
- Mikhael Azilinon
- Aix Marseille Université, INSERM, Institut de Neurosciences des Systèmes (INS) UMR 1106, Marseille, France
- Aix Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Timone University Hospital, CEMEREM, Marseille, France
| | - Huifang E Wang
- Aix Marseille Université, INSERM, Institut de Neurosciences des Systèmes (INS) UMR 1106, Marseille, France
| | - Julia Makhalova
- APHM, Timone University Hospital, CEMEREM, Marseille, France
- APHM, Epileptology and Clinical Neurophysiology Department, Timone Hospital, Marseille, France
| | - Wafaa Zaaraoui
- Aix Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Timone University Hospital, CEMEREM, Marseille, France
| | - Jean-Philippe Ranjeva
- Aix Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Timone University Hospital, CEMEREM, Marseille, France
| | - Fabrice Bartolomei
- Aix Marseille Université, INSERM, Institut de Neurosciences des Systèmes (INS) UMR 1106, Marseille, France
- APHM, Epileptology and Clinical Neurophysiology Department, Timone Hospital, Marseille, France
| | - Maxime Guye
- Aix Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Timone University Hospital, CEMEREM, Marseille, France
| | - Viktor Jirsa
- Aix Marseille Université, INSERM, Institut de Neurosciences des Systèmes (INS) UMR 1106, Marseille, France
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6
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Guichet C, Roger É, Attyé A, Achard S, Mermillod M, Baciu M. Midlife dynamics of white matter architecture in lexical production. Neurobiol Aging 2024; 144:138-152. [PMID: 39357455 DOI: 10.1016/j.neurobiolaging.2024.09.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 09/20/2024] [Accepted: 09/21/2024] [Indexed: 10/04/2024]
Abstract
We aimed to examine the white matter changes associated with lexical production difficulties, beginning in midlife with increased naming latencies. To delay lexical production decline, middle-aged adults may rely on domain-general and language-specific compensatory mechanisms proposed by the LARA model (Lexical Access and Retrieval in Aging). However, the white matter changes supporting these mechanisms remains largely unknown. Using data from the CAMCAN cohort, we employed an unsupervised and data-driven methodology to examine the relationships between diffusion-weighted imaging and lexical production. Our findings indicate that midlife is marked by alterations in brain structure within distributed dorsal, ventral, and anterior cortico-subcortical networks, marking the onset of lexical production decline around ages 53-54. Middle-aged adults may initially adopt a "semantic strategy" to compensate for lexical production challenges, but this strategy seems compromised later (ages 55-60) as semantic control declines. These insights underscore the interplay between domain-general and language-specific processes in the trajectory of lexical production performance in healthy aging and hint at potential biomarkers for language-related neurodegenerative pathologies.
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Affiliation(s)
- Clément Guichet
- Univ. Grenoble Alpes, CNRS LPNC UMR 5105, Grenoble 38000, France
| | - Élise Roger
- Institut Universitaire de Gériatrie de Montréal, Communication and Aging Lab, Montreal, Quebec, Canada; Faculty of Medicine, University of Montreal, Montreal, Quebec, Canada
| | | | - Sophie Achard
- Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP, LJK, Grenoble 38000, France
| | | | - Monica Baciu
- Univ. Grenoble Alpes, CNRS LPNC UMR 5105, Grenoble 38000, France; Neurology Department, CMRR, Grenoble Hospital, Grenoble 38000, France.
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7
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Li Y, Liu P, Lin Q, Li W, Zhang Y, Li J, Li X, Gong Q, Zhang H, Li L, Sima X, Cao D, Huang X, Huang K, Zhou D, An D. Temporopolar blurring signifies abnormalities of white matter in mesial temporal lobe epilepsy. Ann Clin Transl Neurol 2024. [PMID: 39342438 DOI: 10.1002/acn3.52204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 08/19/2024] [Accepted: 08/26/2024] [Indexed: 10/01/2024] Open
Abstract
OBJECTIVE The single-center retrospective cohort study investigated underlying pathogenic mechanisms and clinical significance of patients with temporal lobe epilepsy and hippocampal sclerosis (TLE-HS), in the presence/absence of gray-white matter abnormalities (usually called "blurring"; GMB) in ipsilateral temporopolar region (TPR) on MRI. METHODS The study involved 105 patients with unilateral TLE-HS (60 GMB+ and 45 GMB-) who underwent standard anterior temporal lobectomy, along with 61 healthy controls. Resected specimens were examined under light microscope. With combined T1-weighted and DTI data, we quantitatively compared large-scale morphometric features and exacted diffusion parameters of ipsilateral TPR-related superficial and deep white matter (WM) by atlas-based segmentation. Along-tract analysis was added to detect heterogeneous microstructural alterations at various points along deep WM tracts, which were categorized into inferior longitudinal fasciculus (ILF), uncinate fasciculus (UF), and temporal cingulum. RESULTS Comparable seizure semiology and postoperative seizure outcome were found, while the GMB+ group had significantly higher rate of HS Type 1 and history of febrile seizures, contrasting with significantly lower proportion of interictal contralateral epileptiform discharges, HS Type 2, and increased wasteosomes in hippocampal specimens. Similar morphometric features but greater WM atrophy with more diffusion abnormalities of superficial WM was observed adjacent to ipsilateral TPR in the GMB+ group. Moreover, microstructural alterations resulting from temporopolar GMB were more localized in temporal cingulum while evenly and widely distributed along ILF and UF. INTERPRETATION Temporopolar GMB could signify more severe and widespread microstructural damage of white matter rather than a focal cortical lesion in TLE-HS, affecting selection of surgical procedures.
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Affiliation(s)
- Yuming Li
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Peiwen Liu
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Qiuxing Lin
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Wei Li
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Yingying Zhang
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Jinmei Li
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Xiuli Li
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Heng Zhang
- Department of Neurosurgery, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Luying Li
- Department of Neurosurgery, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Xiutian Sima
- Department of Neurosurgery, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Danyang Cao
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Xiang Huang
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Kailing Huang
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Dong Zhou
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Dongmei An
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, 610041, China
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8
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Qu J, Zhu R, Wu Y, Xu G, Wang D. Abnormal structural‒functional coupling patterning in progressive supranuclear palsy is associated with diverse gradients and histological features. Commun Biol 2024; 7:1195. [PMID: 39341965 PMCID: PMC11439051 DOI: 10.1038/s42003-024-06877-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Accepted: 09/10/2024] [Indexed: 10/01/2024] Open
Abstract
The anatomy of the brain supports inherent processes, fostering mental abilities and eventually facilitating adaptive behavior. Recent studies have shown that progressive supranuclear palsy (PSP) is accompanied by alterations in functional and structural networks. However, how the structure and function of PSP coordinates change is not clear, and the relationships between structural‒functional coupling (SFC) and the gradient of hierarchical structure and cellular histology remain largely unknown. Here, we use neuroimaging data from two independent cohorts and a public histological dataset to investigate the relationships among the cellular histology, hierarchical structure, and SFC of PSP patients. We find that the SFC of the entire cortex in PSP is severely disrupted, with higher coupling in the visual network (VN). Moreover, coupling differences in PSP follow a macroscopic organizational principle from unimodal to transmodal gradients. Finally, we elucidate greater laminar differentiation in VN regions sensitive to SFC changes in PSP, which is related mainly to the higher cellular density and smaller size of the internal-granular layer. In conclusion, our findings provide an interpretable framework for understanding SFC changes in PSP and provide new insights into the consistency of structural and functional changes in PSP regarding hierarchical structure and cellular histology.
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Affiliation(s)
- Junyu Qu
- Department of Radiology, Qilu Hospital of Shandong University; Qilu Medical Imaging Institute of Shandong University, Jinan, China
| | - Rui Zhu
- Department of Radiology, Qilu Hospital of Shandong University; Qilu Medical Imaging Institute of Shandong University, Jinan, China
| | - Yongsheng Wu
- Department of Radiology, Qilu Hospital of Shandong University; Qilu Medical Imaging Institute of Shandong University, Jinan, China
| | - Guihua Xu
- Department of Radiology, Qilu Hospital of Shandong University; Qilu Medical Imaging Institute of Shandong University, Jinan, China
| | - Dawei Wang
- Department of Radiology, Qilu Hospital of Shandong University; Qilu Medical Imaging Institute of Shandong University, Jinan, China.
- Research Institute of Shandong University: Magnetic Field-free Medicine & Functional Imaging, Jinan, China.
- Shandong Key Laboratory: Magnetic Field-free Medicine & Functional Imaging (MF), Jinan, China.
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Carson RG, Leemans A. Quantitative metrics commonly derived from diffusion tractography covary with streamline length: a characterization and method of adjustment. Brain Struct Funct 2024:10.1007/s00429-024-02854-9. [PMID: 39259359 DOI: 10.1007/s00429-024-02854-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Accepted: 08/28/2024] [Indexed: 09/13/2024]
Abstract
Tractography algorithms are used extensively to delineate white matter structures, by operating on the voxel-wise information generated through the application of diffusion tensor imaging (DTI) or other models to diffusion weighted (DW) magnetic resonance imaging (MRI) data. Through statistical modelling, we demonstrate that these methods commonly yield substantial and systematic associations between streamline length and several tractography derived quantitative metrics, such as fractional anisotropy (FA). These associations may be described as piecewise linear. For streamlines shorter than an inflection point (determined for a group of tracts delineated for each individual brain), estimates of FA exhibit a positive linear relation with streamline length. For streamlines longer than the point of inflection, the association is weaker, with the slope of the relationship between streamline length and FA differing only marginally from zero. As the association is most pronounced for a range of streamline lengths encountered typically in DW imaging of the human brain (less than ~ 100 mm), our results suggest that some quantitative metrics derived from diffusion tractography have the potential to mislead, if variations in streamline length are not considered. A method is described, whereby an Akaike information weighted average of linear, Blackman and piecewise linear model predictions, may be used to compensate effectively for the association of FA (and other quantitative metrics) with streamline length, across the entire range of streamline lengths present in each specimen.
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Affiliation(s)
- Richard G Carson
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin 2, Dublin, Ireland.
| | - Alexander Leemans
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, 85500, The Netherlands
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10
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Funk AT, Hassan AAO, Waugh JL. In Humans, Insulo-striate Structural Connectivity is Largely Biased Toward Either Striosome-like or Matrix-like Striatal Compartments. Neurosci Insights 2024; 19:26331055241268079. [PMID: 39280330 PMCID: PMC11402065 DOI: 10.1177/26331055241268079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Accepted: 07/15/2024] [Indexed: 09/18/2024] Open
Abstract
The insula is an integral component of sensory, motor, limbic, and executive functions, and insular dysfunction is associated with numerous human neuropsychiatric disorders. Insular efferents project widely, but insulo-striate projections are especially numerous. The targets of these insulo-striate projections are organized into tissue compartments, the striosome and matrix. These striatal compartments have distinct embryologic origins, afferent and efferent connectivity, dopamine pharmacology, and susceptibility to injury. Striosome and matrix appear to occupy separate sets of cortico-striato-thalamo-cortical loops, so a bias in insulo-striate projections toward one compartment may also embed an insular subregion in distinct regulatory and functional networks. Compartment-specific mapping of insulo-striate structural connectivity is sparse; the insular subregions are largely unmapped for compartment-specific projections. In 100 healthy adults, diffusion tractography was utilized to map and quantify structural connectivity between 19 structurally-defined insular subregions and each striatal compartment. Insulo-striate streamlines that reached striosome-like and matrix-like voxels were concentrated in distinct insular zones (striosome: rostro- and caudoventral; matrix: caudodorsal) and followed different paths to reach the striatum. Though tractography was generated independently in each hemisphere, the spatial distribution and relative bias of striosome-like and matrix-like streamlines were highly similar in the left and right insula. 16 insular subregions were significantly biased toward 1 compartment: 7 toward striosome-like voxels and 9 toward matrix-like voxels. Striosome-favoring bundles had significantly higher streamline density, especially from rostroventral insular subregions. The biases in insulo-striate structural connectivity that were identified mirrored the compartment-specific biases identified in prior studies that utilized injected tract tracers, cytoarchitecture, or functional MRI. Segregating insulo-striate structural connectivity through either striosome or matrix may be an anatomic substrate for functional specialization among the insular subregions.
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Affiliation(s)
- Adrian T Funk
- Division of Pediatric Neurology, Department of Pediatrics, University of Texas Southwestern, Dallas, TX, USA
| | - Asim AO Hassan
- Department of Natural Sciences and Mathematics, University of Texas at Dallas, TX, USA
| | - Jeff L Waugh
- Division of Pediatric Neurology, Department of Pediatrics, University of Texas Southwestern, Dallas, TX, USA
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
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11
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Aguayo-González JF, Ehrlich-Lopez H, Concha L, Rivera M. Light-weight neural network for intra-voxel structure analysis. Front Neuroinform 2024; 18:1277050. [PMID: 39315001 PMCID: PMC11417038 DOI: 10.3389/fninf.2024.1277050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Accepted: 08/16/2024] [Indexed: 09/25/2024] Open
Abstract
We present a novel neural network-based method for analyzing intra-voxel structures, addressing critical challenges in diffusion-weighted MRI analysis for brain connectivity and development studies. The network architecture, called the Local Neighborhood Neural Network, is designed to use the spatial correlations of neighboring voxels for an enhanced inference while reducing parameter overhead. Our model exploits these relationships to improve the analysis of complex structures and noisy data environments. We adopt a self-supervised approach to address the lack of ground truth data, generating signals of voxel neighborhoods to integrate the training set. This eliminates the need for manual annotations and facilitates training under realistic conditions. Comparative analyses show that our method outperforms the constrained spherical deconvolution (CSD) method in quantitative and qualitative validations. Using phantom images that mimic in vivo data, our approach improves angular error, volume fraction estimation accuracy, and success rate. Furthermore, a qualitative comparison of the results in actual data shows a better spatial consistency of the proposed method in areas of real brain images. This approach demonstrates enhanced intra-voxel structure analysis capabilities and holds promise for broader application in various imaging scenarios.
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Affiliation(s)
| | | | - Luis Concha
- Department of Behavioral and Cognitive Neurobiology, Institute of Neurobiology, National Autonomous University of Mexico, Queretaro, Mexico
| | - Mariano Rivera
- Centro de Investigacion en Matematicas, Guanajuato, Mexico
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12
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Jeong JW, Lee MH, Behen M, Uda H, Gjolaj N, Luat A, Asano E, Juhász C. Quantitative phenotyping of verbal and non-verbal cognitive impairment using diffusion-weighted MRI connectome: Preliminary study of the crowding effect in children with left hemispheric epilepsy. Epilepsy Behav 2024; 160:110009. [PMID: 39241639 DOI: 10.1016/j.yebeh.2024.110009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 07/22/2024] [Accepted: 08/20/2024] [Indexed: 09/09/2024]
Abstract
The "crowding" effect (CE), wherein verbal functions are preserved presumably at the expense of nonverbal functions, which diminish following inter-hemispheric transfer of language functions, is recognized as a specific aspect of functional reorganization, offering an insight about neural plasticity in children with neural insult to the dominant hemisphere. CE is hypothesized as a marker for language preservation or improvement after left-hemispheric injury, yet it remains challenging to fully discern it in preoperative evaluation. We present a novel DWI connectome (DWIC) approach to predict the presence of CE in 24 drug-resistant epilepsy (DRE) patients with a left-hemispheric focus and 29 young healthy controls. Psychometry-driven DWIC analysis was applied to create verbal and non-verbal modular networks. Local efficiency (LE) was assessed at individual regions of the two networks and its Z-score was compared to predict the presence of CE. Compared with a traditional organization (TO) group, wherein verbal functions are adversely affected, while non-verbal functions are preserved, the CE group showed significantly higher Z-scores in verbal network and significantly lower Z-scores in non-verbal network, corresponding to network reorganization in CE. A larger number of antiseizure drugs was significantly associated with more decreased Z-score in the right non-verbal network of the CE group and left verbal network of the TO group. These findings hold great potential to identify DRE patients whose verbal/language skills may over time be preserved due to effective inter-hemispheric reorganization and identify those whose verbal/language impairments may persist due to lack of inter-hemispheric reorganization.
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Affiliation(s)
- Jeong-Won Jeong
- Department of Pediatrics, Wayne State University, Detroit, MI, United States; Translational Imaging Laboratory, University Health Center, Detroit, MI, United States; Department of Neurology, Wayne State University, Detroit, MI, United States; Translational Neuroscience Program, Wayne State University, Detroit, MI, United States.
| | - Min-Hee Lee
- Department of Pediatrics, Wayne State University, Detroit, MI, United States; Translational Imaging Laboratory, University Health Center, Detroit, MI, United States
| | - Michael Behen
- Department of Pediatrics, Wayne State University, Detroit, MI, United States; Department of Neurology, Wayne State University, Detroit, MI, United States
| | - Hiroshi Uda
- Department of Pediatrics, Wayne State University, Detroit, MI, United States
| | - Nore Gjolaj
- Department of Pediatrics, Wayne State University, Detroit, MI, United States
| | - Aimee Luat
- Department of Neurology, Wayne State University, Detroit, MI, United States; Department of Pediatrics, Central Michigan University, Mt. Pleasant, MI, United States
| | - Eishi Asano
- Department of Pediatrics, Wayne State University, Detroit, MI, United States; Translational Imaging Laboratory, University Health Center, Detroit, MI, United States; Department of Neurology, Wayne State University, Detroit, MI, United States; Translational Neuroscience Program, Wayne State University, Detroit, MI, United States
| | - Csaba Juhász
- Department of Pediatrics, Wayne State University, Detroit, MI, United States; Translational Imaging Laboratory, University Health Center, Detroit, MI, United States; Department of Neurology, Wayne State University, Detroit, MI, United States; Translational Neuroscience Program, Wayne State University, Detroit, MI, United States
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13
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Sierra-Silvestre E, Smith RE, Andrade RJ, Kennedy B, Coppieters MW. Microstructural changes in the median and ulnar nerve in people with and without diabetic neuropathy in their hands: A cross-sectional diffusion MRI study. Eur J Radiol 2024; 181:111721. [PMID: 39260209 DOI: 10.1016/j.ejrad.2024.111721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 05/29/2024] [Accepted: 09/03/2024] [Indexed: 09/13/2024]
Abstract
PURPOSE Diffusion weighted imaging (DWI) has revealed microstructural changes in lower limb nerves in people with diabetic neuropathy. Microstructural changes in upper limb nerves using DWI in people with diabetes have not yet been explored. METHODS This cross-sectional study aimed to quantify and compare the microstructure of the median and ulnar nerve in people without diabetes (n = 10), people with diabetes without distal symmetrical polyneuropathy (DSPN; n = 10), people with DSPN in the lower limbs only (DSPN FEET ONLY; n = 12), and people with DSPN in the upper and lower limbs (DSPN HANDS & FEET; n = 9). DSPN diagnosis included electrodiagnosis and corneal confocal microscopy. Tensor metrics, such as fractional anisotropy, radial diffusivity and axial diffusivity, and constrained spherical deconvolution metrics, such as dispersion and complexity, were calculated. Linear mixed-models were used to quantify DWI metrics from multiple models in median and ulnar nerves across the groups, and to evaluate potential differences in metrics at the wrist and elbow based on the principle of a distal-to-proximal disease progression. RESULTS Tensor metrics revealed microstructural abnormalities in the median and ulnar nerve in people with DSPN HANDS & FEET, and also already in DSPN FEET ONLY. There were significant negative correlations between electrodiagnostic parameters and tensor metrics. A distal-to-proximal pattern was more pronounced in the median nerve. Non-tensor metrics showed early microstructural changes in people with diabetes without DSPN. CONCLUSION Compared to people without diabetes, microstructural changes in upper limb nerves can be identified in people with diabetes with and without DSPN, even before symptoms occur.
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Affiliation(s)
- Eva Sierra-Silvestre
- School of Health Sciences and Social Work, Griffith University, Brisbane, Australia; Amsterdam Movement Sciences - Program Musculoskeletal Health, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK. https://twitter.com/esiesil
| | - Robert E Smith
- The Florey Institute of Neuroscience and Mental Health, Heidelberg, Australia; The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia
| | - Ricardo J Andrade
- School of Health Sciences and Social Work, Griffith University, Brisbane, Australia; Movement - Interactions - Performance (MIP), Nantes University, Nantes, France. https://twitter.com/jacobofhume
| | - Ben Kennedy
- Mermaid Beach Radiology, Gold Coast, Australia
| | - Michel W Coppieters
- School of Health Sciences and Social Work, Griffith University, Brisbane, Australia; Amsterdam Movement Sciences - Program Musculoskeletal Health, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. https://twitter.com/michelcoppie
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14
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Hechler A, Kuchling J, Müller-Jensen L, Klag J, Paul F, Prüss H, Finke C. Hippocampal hub failure is linked to long-term memory impairment in anti-NMDA-receptor encephalitis: insights from structural connectome graph theoretical network analysis. J Neurol 2024; 271:5886-5898. [PMID: 38977462 PMCID: PMC11377655 DOI: 10.1007/s00415-024-12545-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 06/22/2024] [Accepted: 06/26/2024] [Indexed: 07/10/2024]
Abstract
BACKGROUND Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is characterized by distinct structural and functional brain alterations, predominantly affecting the medial temporal lobes and the hippocampus. Structural connectome analysis with graph-based investigations of network properties allows for an in-depth characterization of global and local network changes and their relationship with clinical deficits in NMDAR encephalitis. METHODS Structural networks from 61 NMDAR encephalitis patients in the post-acute stage (median time from acute hospital discharge: 18 months) and 61 age- and sex-matched healthy controls (HC) were analyzed using diffusion-weighted imaging (DWI)-based probabilistic anatomically constrained tractography and volumetry of a selection of subcortical and white matter brain volumes was performed. We calculated global, modular, and nodal graph measures with special focus on default-mode network, medial temporal lobe, and hippocampus. Pathologically altered metrics were investigated regarding their potential association with clinical course, disease severity, and cognitive outcome. RESULTS Patients with NMDAR encephalitis showed regular global graph metrics, but bilateral reductions of hippocampal node strength (left: p = 0.049; right: p = 0.013) and increased node strength of right precuneus (p = 0.013) compared to HC. Betweenness centrality was decreased for left-sided entorhinal cortex (p = 0.042) and left caudal middle frontal gyrus (p = 0.037). Correlation analyses showed a significant association between reduced left hippocampal node strength and verbal long-term memory impairment (p = 0.021). We found decreased left (p = 0.013) and right (p = 0.001) hippocampal volumes that were associated with hippocampal node strength (left p = 0.009; right p < 0.001). CONCLUSIONS Focal network property changes of the medial temporal lobes indicate hippocampal hub failure that is associated with memory impairment in NMDAR encephalitis at the post-acute stage, while global structural network properties remain unaltered. Graph theory analysis provides new pathophysiological insight into structural network changes and their association with persistent cognitive deficits in NMDAR encephalitis.
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Affiliation(s)
- André Hechler
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- TUM-Neuroimaging Center, Technische Universitaet Muenchen, Munich, Germany
| | - Joseph Kuchling
- Department of Neurology and Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Leonie Müller-Jensen
- Department of Neurology and Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Johanna Klag
- Department of Neurology and Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Friedemann Paul
- Department of Neurology and Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité, Universitätsmedizin Berlin, Berlin, Germany
- Neurocure Cluster of Excellence, NeuroCure Clinical Research Center, Charité, Berlin Institute of Health, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Harald Prüss
- Department of Neurology and Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Berlin, Germany
| | - Carsten Finke
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany.
- Department of Neurology and Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.
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15
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Xu R, Wang X, Zhu S, Jiang B, Wan J, Ma J, Yu Y, Yu L, Fang Q, Hu C, Zhu M. Assessment of Cerebral White Matter Involvement in Amyotrophic Lateral Sclerosis Patients With Disease Progression and Cognitive Impairment by Fixel-Based Analysis and Neurite Orientation Dispersion and Density Imaging. J Magn Reson Imaging 2024; 60:900-908. [PMID: 38059522 DOI: 10.1002/jmri.29171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Revised: 11/17/2023] [Accepted: 11/20/2023] [Indexed: 12/08/2023] Open
Abstract
BACKGROUND Previous studies using emerging diffusion MRI techniques have revealed damage to the white matter (WM) microstructure in amyotrophic lateral sclerosis (ALS), particularly the influence of crossed fibers, but there is a lack of subgroup analyses. PURPOSE To detect WM microstructural changes in ALS patients using fixel-based analysis (FBA) and neurite orientation dispersion and density imaging (NODDI) MRI. STUDY TYPE Prospective. POPULATION Thirty-six ALS patients (aged 60.50 ± 9.5 years) and 25 healthy controls (HCs) (aged 58.90 ± 8.1 years). FIELD STRENGTH/SEQUENCE 3 T; NODDI and FBA (b-values = 0, 1000, and 2500 seconds/mm2). ASSESSMENT Subgroups were performed according to progression rate and cognition, including fast and slow progression (FP/SP), ALS with and without cognitive impairment (ALS-ci/ALS-nci). Fiber density (FD), fiber-bundle cross-section (FC), combined fiber density and cross-section (FDC), neurite density index (NDI), orientation dispersion index (ODI), isotropic volume fraction (ISO), and fractional anisotropy (FA) were calculated and their correlation with clinical variables examined. STATISTICAL TESTING Chi-square test, Mann-Whitney U test, two-sample t test, partial correlation analysis, and false discovery rate (FDR) corrected. A P-value <0.05 was considered significant. RESULTS ALS patients had lower FD and FDC values predominantly in the corticospinal tract (CST) and corpus callosum (CC) regions, as well as lower NDI value in the CC, radial crown, and internal capsule compared to HCs. Subgroup analysis based on progression rate and cognitive function showed significant differences in FBA results. The FC in the right CST region was significantly lower in the FP than SP, and the FD in the CC region was significantly lower in the ALS-ci than ALS-nci. Furthermore, a negative correlation was found between the mean FC value and the rate of progression in ALS patients (r = -0.408). DATA CONCLUSION FBA is a powerful tool for detecting complex cerebral WM microstructural damage for evaluating ALS cognition and disease progression.
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Affiliation(s)
- Rui Xu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Ximing Wang
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Sijia Zhu
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Bin Jiang
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Jiayi Wan
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Jiali Ma
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Yixing Yu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Liqiang Yu
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Qi Fang
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Chunhong Hu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Mo Zhu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
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Mills EP, Bosma RL, Rogachov A, Cheng JC, Osborne NR, Kim JA, Besik A, Bhatia A, Davis KD. Pretreatment Brain White Matter Integrity Associated With Neuropathic Pain Relief and Changes in Temporal Summation of Pain Following Ketamine. THE JOURNAL OF PAIN 2024; 25:104536. [PMID: 38615801 DOI: 10.1016/j.jpain.2024.104536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 03/07/2024] [Accepted: 04/09/2024] [Indexed: 04/16/2024]
Abstract
Neuropathic pain (NP) is a prevalent condition often associated with heightened pain responsiveness suggestive of central sensitization. Neuroimaging biomarkers of treatment outcomes may help develop personalized treatment strategies, but white matter (WM) properties have been underexplored for this purpose. Here we assessed whether WM pathways of the default mode network (DMN: medial prefrontal cortex [mPFC], posterior cingulate cortex, and precuneus) and descending pain modulation system (periaqueductal gray [PAG]) are associated with ketamine analgesia and attenuated temporal summation of pain (TSP, reflecting central sensitization) in NP. We used a fixel-based analysis of diffusion-weighted imaging data to evaluate WM microstructure (fiber density [FD]) and macrostructure (fiber bundle cross-section) within the DMN and mPFC-PAG pathways in 70 individuals who underwent magnetic resonance imaging and TSP testing; 35 with NP who underwent ketamine treatment and 35 age- and sex-matched pain-free individuals. Individuals with NP were assessed before and 1 month after treatment; those with ≥30% pain relief were considered responders (n = 18), or otherwise as nonresponders (n = 17). We found that WM structure within the DMN and mPFC-PAG pathways did not differentiate responders from nonresponders. However, pretreatment FD in the anterior limb of the internal capsule correlated with pain relief (r=.48). Moreover, pretreatment FD in the DMN (left mPFC-precuneus/posterior cingulate cortex; r=.52) and mPFC-PAG (r=.42) negatively correlated with changes in TSP. This suggests that WM microstructure in the DMN and mPFC-PAG pathway is associated with the degree to which ketamine reduces central sensitization. Thus, fixel metrics of WM structure may hold promise to predict ketamine NP treatment outcomes. PERSPECTIVE: We used advanced fixel-based analyses of MRI diffusion-weighted imaging data to identify pretreatment WM microstructure associated with ketamine outcomes, including analgesia and markers of attenuated central sensitization. Exploring associations between brain structure and treatment outcomes could contribute to a personalized approach to treatment for individuals with NP.
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Affiliation(s)
- Emily P Mills
- Division of Brain, Imaging, and Behaviour, Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada
| | - Rachael L Bosma
- Division of Brain, Imaging, and Behaviour, Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada
| | - Anton Rogachov
- Division of Brain, Imaging, and Behaviour, Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Joshua C Cheng
- Division of Brain, Imaging, and Behaviour, Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Natalie R Osborne
- Division of Brain, Imaging, and Behaviour, Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Junseok A Kim
- Division of Brain, Imaging, and Behaviour, Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Ariana Besik
- Division of Brain, Imaging, and Behaviour, Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada
| | - Anuj Bhatia
- Department of Anesthesia and Pain Management, University Health Network, Toronto, Ontario, Canada; Department of Anesthesia, University of Toronto, Toronto, Ontario, Canada
| | - Karen D Davis
- Division of Brain, Imaging, and Behaviour, Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Surgery, University of Toronto, Toronto, Ontario, Canada
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Wu Z, Weng X, Shen J, Hong M. Voxel-Wise Fusion of 3T and 7T Diffusion MRI Data to Extract more Accurate Fiber Orientations. Brain Topogr 2024; 37:684-698. [PMID: 38568279 DOI: 10.1007/s10548-024-01046-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 03/12/2024] [Indexed: 09/14/2024]
Abstract
While 7T diffusion magnetic resonance imaging (dMRI) has high spatial resolution, its diffusion imaging quality is usually affected by signal loss due to B1 inhomogeneity, T2 decay, susceptibility, and chemical shift. In contrast, 3T dMRI has relative higher diffusion angular resolution, but lower spatial resolution. Combination of 3T and 7T dMRI, thus, may provide more detailed and accurate information about the voxel-wise fiber orientations to better understand the structural brain connectivity. However, this topic has not yet been thoroughly explored until now. In this study, we explored the feasibility of fusing 3T and 7T dMRI data to extract voxel-wise quantitative parameters at higher spatial resolution. After 3T and 7T dMRI data was preprocessed, respectively, 3T dMRI volumes were coregistered into 7T dMRI space. Then, 7T dMRI data was harmonized to the coregistered 3T dMRI B0 (b = 0) images. Last, harmonized 7T dMRI data was fused with 3T dMRI data according to four fusion rules proposed in this study. We employed high-quality 3T and 7T dMRI datasets (N = 24) from the Human Connectome Project to test our algorithms. The diffusion tensors (DTs) and orientation distribution functions (ODFs) estimated from the 3T-7T fused dMRI volumes were statistically analyzed. More voxels containing multiple fiber populations were found from the fused dMRI data than from 7T dMRI data set. Moreover, extra fiber directions were extracted in temporal brain regions from the fused dMRI data at Otsu's thresholds of quantitative anisotropy, but could not be extracted from 7T dMRI dataset. This study provides novel algorithms to fuse intra-subject 3T and 7T dMRI data for extracting more detailed information of voxel-wise quantitative parameters, and a new perspective to build more accurate structural brain networks.
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Affiliation(s)
- Zhanxiong Wu
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, Zhejiang, 310018, China
| | - Xinmeng Weng
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, Zhejiang, 310018, China
| | - Jian Shen
- Neurosurgery Department, The First Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang, China
| | - Ming Hong
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, Zhejiang, 310018, China.
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18
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Takemura H, Kaneko T, Sherwood CC, Johnson GA, Axer M, Hecht EE, Ye FQ, Leopold DA. A prominent vertical occipital white matter fasciculus unique to primate brains. Curr Biol 2024; 34:3632-3643.e4. [PMID: 38991613 PMCID: PMC11338705 DOI: 10.1016/j.cub.2024.06.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 06/09/2024] [Accepted: 06/11/2024] [Indexed: 07/13/2024]
Abstract
Vision in humans and other primates enlists parallel processing streams in the dorsal and ventral visual cortex, known to support spatial and object processing, respectively. These streams are bridged, however, by a prominent white matter tract, the vertical occipital fasciculus (VOF), identified in both classical neuroanatomy and recent diffusion-weighted magnetic resonance imaging (dMRI) studies. Understanding the evolution of the VOF may shed light on its origin, function, and role in visually guided behaviors. To this end, we acquired high-resolution dMRI data from the brains of select mammalian species, including anthropoid and strepsirrhine primates, a tree shrew, rodents, and carnivores. In each species, we attempted to delineate the VOF after first locating the optic radiations in the occipital white matter. In all primate species examined, the optic radiation was flanked laterally by a prominent and coherent white matter fasciculus recognizable as the VOF. By contrast, the equivalent analysis applied to four non-primate species from the same superorder as primates (tree shrew, ground squirrel, paca, and rat) failed to reveal white matter tracts in the equivalent location. Clear evidence for a VOF was also absent in two larger carnivore species (ferret and fox). Although we cannot rule out the existence of minor or differently organized homologous fiber pathways in the non-primate species, the results suggest that the VOF has greatly expanded, or possibly emerged, in the primate lineage. This adaptation likely facilitated the evolution of unique visually guided behaviors in primates, with direct impacts on manual object manipulation, social interactions, and arboreal locomotion.
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Affiliation(s)
- Hiromasa Takemura
- Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, 38 Nishigonaka Myodaiji, Okazaki-shi, Aichi 444-8585, Japan; The Graduate Institute for Advanced Studies, SOKENDAI, Shonan Village, Hayama-cho, Kanagawa 240-0193, Japan; Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, 1-4 Yamadaoka, Suita-shi, Osaka 565-0871, Japan.
| | - Takaaki Kaneko
- Center for the Evolutionary Origins of Human Behavior, Kyoto University, 41-2 Kanrin, Inuyama-shi, Aichi 484-8506, Japan; Division of Behavioral Development, Department of System Neuroscience, National Institute for Physiological Sciences, 38 Nishigonaka Myodaiji, Okazaki-shi, Aichi, Japan
| | - Chet C Sherwood
- Department of Anthropology, The George Washington University, 800 22nd St. NW, Washington, DC 20052, USA
| | - G Allan Johnson
- Department of Radiology, Duke Center for In Vivo Microscopy, Duke Medical Center, 311 Research Drive, Durham, NC 27710, USA; Department of Biomedical Engineering, Duke University, 101 Science Dive., Durham, NC 27705, USA
| | - Markus Axer
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich 52425, Germany; Department of Physics, School of Mathematics and Natural Sciences, University of Wuppertal, Gaußstraße 20 42119, Wuppertal, Germany
| | - Erin E Hecht
- Department of Human Evolutionary Biology, Harvard University, 11 Divinity Avenue, Cambridge, MA 02138, USA
| | - Frank Q Ye
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD 20814, USA
| | - David A Leopold
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD 20814, USA; Systems Neurodevelopment Laboratory, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20814, USA.
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19
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Bernstein A, Arias JC, Howell C, French S, Guzman G, Bruck D, Berman S, Leon L, Pacanowski J, Tan TW, Altbach M, Trouard T, Weinkauf C. Improved cognition and preserved hippocampal fractional anisotropy in subjects undergoing carotid endarterectomy "CEA preserves cognition & hippocampal structure". J Stroke Cerebrovasc Dis 2024; 33:107926. [PMID: 39154784 DOI: 10.1016/j.jstrokecerebrovasdis.2024.107926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 07/30/2024] [Accepted: 08/09/2024] [Indexed: 08/20/2024] Open
Abstract
OBJECTIVES A growing body of data indicates that extracranial carotid artery disease (ECAD) can contribute to cognitive impairment. However, there have been mixed reports regarding the benefit of carotid endarterectomy (CEA) as it relates to preserving cognitive function. In this work, diffusion magnetic resonance imaging (dMRI) and neurocognitive testing are used to provide insight into structural and functional brain changes that occur in subjects with significant carotid artery stenosis, as well as changes that occur in response to CEA. MATERIALS AND METHODS The study design was a prospective, non-randomized, controlled study that enrolled patients with asymptomatic carotid stenosis. Thirteen subjects had severe ECAD (≥70% stenosis in at least one carotid artery) and were scheduled to undergo surgery. Thirteen had asymptomatic ECAD with <70% stenosis, therefore not requiring surgery. All subjects underwent neurocognitive testing using the Montreal Cognitive Assessment test (MoCA) and high angular resolution, multi-shell diffusion magnetic resonance imaging (dMRI) of the brain at baseline and at four-six months follow-up. Changes in MoCA scores as well as in Fractional anisotropy (FA) along the hippocampus were compared at baseline and follow-up. RESULTS At baseline, FA was significantly lower along the ipsilateral hippocampus in subjects with severe ECAD compared to subjects without severe ECAD. MoCA scores were lower in these individuals, but this did not reach statistical significance. At follow-up, MoCA scores increased significantly in subjects who underwent CEA and remained statistically equal in control subjects that did not have CEA. FA remained unchanged in the CEA group and decreased in the control group. CONCLUSIONS This study suggests that CEA improves cognition and preserves hippocampal white matter structure compared to control subjects not undergoing CEA.
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Affiliation(s)
- Adam Bernstein
- Department of Biomedical Engineering, University of Arizona, Tucson, Arizona 85721, United States.
| | - Juan C Arias
- Department of Surgery, University of Arizona, Tucson, Arizona 85721, United States.
| | - Caronae Howell
- Department of Surgery, University of Arizona, Tucson, Arizona 85721, United States.
| | - Scott French
- Department of Surgery, University of Arizona, Tucson, Arizona 85721, United States.
| | - Gloria Guzman
- Department of Medical Imaging, University of Arizona, Tucson, Arizona 85721, United States.
| | - Denise Bruck
- Department of Medical Imaging, University of Arizona, Tucson, Arizona 85721, United States.
| | - Scott Berman
- Department of Surgery, University of Arizona, Tucson, Arizona 85721, United States; Pima Heart and Vascular Physicians, Tucson, Arizona 85704, United States.
| | - Luis Leon
- Department of Surgery, University of Arizona, Tucson, Arizona 85721, United States; Pima Heart and Vascular Physicians, Tucson, Arizona 85704, United States.
| | - John Pacanowski
- Department of Surgery, University of Arizona, Tucson, Arizona 85721, United States; Pima Heart and Vascular Physicians, Tucson, Arizona 85704, United States.
| | - Tze-Woei Tan
- Department of Surgery, University of Arizona, Tucson, Arizona 85721, United States.
| | - Maria Altbach
- Department of Medical Imaging, University of Arizona, Tucson, Arizona 85721, United States.
| | - Theodore Trouard
- Department of Biomedical Engineering, University of Arizona, Tucson, Arizona 85721, United States; Department of Medical Imaging, University of Arizona, Tucson, Arizona 85721, United States.
| | - Craig Weinkauf
- Department of Surgery, University of Arizona, Tucson, Arizona 85721, United States.
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20
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Barjuan L, Soriano J, Serrano MÁ. Optimal navigability of weighted human brain connectomes in physical space. Neuroimage 2024; 297:120703. [PMID: 38936648 DOI: 10.1016/j.neuroimage.2024.120703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 06/17/2024] [Accepted: 06/21/2024] [Indexed: 06/29/2024] Open
Abstract
Communication protocols in the brain connectome describe how to transfer information from one region to another. Typically, these protocols hinge on either the spatial distances between brain regions or the intensity of their connections. Yet, none of them combine both factors to achieve optimal efficiency. Here, we introduce a continuous spectrum of decentralized routing strategies that integrates link weights and the spatial embedding of connectomes to route signal transmission. We implemented the protocols on connectomes from individuals in two cohorts and on group-representative connectomes designed to capture weighted connectivity properties. We identified an intermediate domain of routing strategies, a sweet spot, where navigation achieves maximum communication efficiency at low transmission cost. This phenomenon is robust and independent of the particular configuration of weights. Our findings suggest an interplay between the intensity of neural connections and their topology and geometry that amplifies communicability, where weights play the role of noise in a stochastic resonance phenomenon. Such enhancement may support more effective responses to external and internal stimuli, underscoring the intricate diversity of brain functions.
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Affiliation(s)
- Laia Barjuan
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, Martí i Franquès 1, E-08028 Barcelona, Spain; Universitat de Barcelona Institute of Complex Systems (UBICS), Universitat de Barcelona, Martí i Franquès 1, E-08028, Barcelona, Spain
| | - Jordi Soriano
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, Martí i Franquès 1, E-08028 Barcelona, Spain; Universitat de Barcelona Institute of Complex Systems (UBICS), Universitat de Barcelona, Martí i Franquès 1, E-08028, Barcelona, Spain
| | - M Ángeles Serrano
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, Martí i Franquès 1, E-08028 Barcelona, Spain; Universitat de Barcelona Institute of Complex Systems (UBICS), Universitat de Barcelona, Martí i Franquès 1, E-08028, Barcelona, Spain; ICREA, Pg. Lluís Companys 23, E-08010 Barcelona, Spain.
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21
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Jossinger S, Yablonski M, Amir O, Ben-Shachar M. The Contributions of the Cerebellar Peduncles and the Frontal Aslant Tract in Mediating Speech Fluency. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2024; 5:676-700. [PMID: 39175785 PMCID: PMC11338307 DOI: 10.1162/nol_a_00098] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 12/23/2022] [Indexed: 08/24/2024]
Abstract
Fluent speech production is a complex task that spans multiple processes, from conceptual framing and lexical access, through phonological encoding, to articulatory control. For the most part, imaging studies portraying the neural correlates of speech fluency tend to examine clinical populations sustaining speech impairments and focus on either lexical access or articulatory control, but not both. Here, we evaluated the contribution of the cerebellar peduncles to speech fluency by measuring the different components of the process in a sample of 45 neurotypical adults. Participants underwent an unstructured interview to assess their natural speaking rate and articulation rate, and completed timed semantic and phonemic fluency tasks to assess their verbal fluency. Diffusion magnetic resonance imaging with probabilistic tractography was used to segment the bilateral cerebellar peduncles (CPs) and frontal aslant tract (FAT), previously associated with speech production in clinical populations. Our results demonstrate distinct patterns of white matter associations with different fluency components. Specifically, verbal fluency is associated with the right superior CP, whereas speaking rate is associated with the right middle CP and bilateral FAT. No association is found with articulation rate in these pathways, in contrast to previous findings in persons who stutter. Our findings support the contribution of the cerebellum to aspects of speech production that go beyond articulatory control, such as lexical access, pragmatic or syntactic generation. Further, we demonstrate that distinct cerebellar pathways dissociate different components of speech fluency in neurotypical speakers.
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Affiliation(s)
- Sivan Jossinger
- The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel
| | - Maya Yablonski
- The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel
| | - Ofer Amir
- Department of Communication Disorders, Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Michal Ben-Shachar
- The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel
- The Department of English Literature and Linguistics, Bar-Ilan University, Ramat-Gan, Israel
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22
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Drabek-Maunder ER, Mankad K, Aquilina K, Dean JA, Nisbet A, Clark CA. Using diffusion MRI to understand white matter damage and the link between brain microstructure and cognitive deficits in paediatric medulloblastoma patients. Eur J Radiol 2024; 177:111562. [PMID: 38901074 DOI: 10.1016/j.ejrad.2024.111562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 05/09/2024] [Accepted: 06/10/2024] [Indexed: 06/22/2024]
Abstract
PURPOSE Survivors of medulloblastoma face a range of challenges after treatment, involving behavioural, cognitive, language and motor skills. Post-treatment outcomes are associated with structural changes within the brain resulting from both the tumour and the treatment. Diffusion magnetic resonance imaging (MRI) has been used to investigate the microstructure of the brain. In this review, we aim to summarise the literature on diffusion MRI in patients treated for medulloblastoma and discuss future directions on how diffusion imaging can be used to improve patient quality. METHOD This review summarises the current literature on medulloblastoma in children, focusing on the impact of both the tumour and its treatment on brain microstructure. We review studies where diffusion MRI has been correlated with either treatment characteristics or cognitive outcomes. We discuss the role diffusion MRI has taken in understanding the relationship between microstructural damage and cognitive and behavioural deficits. RESULTS We identified 35 studies that analysed diffusion MRI changes in patients treated for medulloblastoma. The majority of these studies found significant group differences in measures of brain microstructure between patients and controls, and some of these studies showed associations between microstructure and neurocognitive outcomes, which could be influenced by patient characteristics (e.g. age), treatment, radiation dose and treatment type. CONCLUSIONS In future, studies would benefit from being able to separate microstructural white matter damage caused by the tumour, tumour-related complications and treatment. Additionally, advanced diffusion modelling methods can be explored to understand and describe microstructural changes to white matter.
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Affiliation(s)
- Emily R Drabek-Maunder
- UCL Great Ormond Street Institute of Child Health, 30 Guildford Street, London WC1N 1EH, UK; UCL Dept of Medical Physics and Biomedical Engineering, Malet Place, Gower St, London WC1E 6BT, UK; Great Ormond Street Hospital for Children, Great Ormond St, London WC1N 3JH, UK.
| | - Kshitij Mankad
- UCL Great Ormond Street Institute of Child Health, 30 Guildford Street, London WC1N 1EH, UK; Great Ormond Street Hospital for Children, Great Ormond St, London WC1N 3JH, UK
| | - Kristian Aquilina
- UCL Great Ormond Street Institute of Child Health, 30 Guildford Street, London WC1N 1EH, UK; Great Ormond Street Hospital for Children, Great Ormond St, London WC1N 3JH, UK
| | - Jamie A Dean
- UCL Dept of Medical Physics and Biomedical Engineering, Malet Place, Gower St, London WC1E 6BT, UK
| | - Andrew Nisbet
- UCL Dept of Medical Physics and Biomedical Engineering, Malet Place, Gower St, London WC1E 6BT, UK
| | - Chris A Clark
- UCL Great Ormond Street Institute of Child Health, 30 Guildford Street, London WC1N 1EH, UK; Great Ormond Street Hospital for Children, Great Ormond St, London WC1N 3JH, UK
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23
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Calixto C, Taymourtash A, Karimi D, Snoussi H, Velasco-Annis C, Jaimes C, Gholipour A. Advances in Fetal Brain Imaging. Magn Reson Imaging Clin N Am 2024; 32:459-478. [PMID: 38944434 PMCID: PMC11216711 DOI: 10.1016/j.mric.2024.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2024]
Abstract
Over the last 20 years, there have been remarkable developments in fetal brain MR imaging analysis methods. This article delves into the specifics of structural imaging, diffusion imaging, functional MR imaging, and spectroscopy, highlighting the latest advancements in motion correction, fetal brain development atlases, and the challenges and innovations. Furthermore, this article explores the clinical applications of these advanced imaging techniques in comprehending and diagnosing fetal brain development and abnormalities.
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Affiliation(s)
- Camilo Calixto
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA.
| | - Athena Taymourtash
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Spitalgasse 23, Wien 1090, Austria
| | - Davood Karimi
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - Haykel Snoussi
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - Clemente Velasco-Annis
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - Camilo Jaimes
- Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA; Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02215, USA
| | - Ali Gholipour
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
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24
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Ciceri T, De Luca A, Agarwal N, Arrigoni F, Peruzzo D. A framework for optimizing the acquisition protocol multishell diffusion-weighted imaging for multimodel assessment. NMR IN BIOMEDICINE 2024; 37:e5141. [PMID: 38520215 DOI: 10.1002/nbm.5141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 11/22/2023] [Accepted: 02/15/2024] [Indexed: 03/25/2024]
Abstract
Complementary aspects of tissue microstructure can be studied with diffusion-weighted imaging (DWI). However, there is no consensus on how to design a diffusion acquisition protocol for multiple models within a clinically feasible time. The purpose of this study is to provide a flexible framework that is able to optimize the shell acquisition protocol given a set of DWI models. Eleven healthy subjects underwent an extensive DWI acquisition protocol, including 15 candidate shells, ranging from 10 to 3500 s/mm2. The proposed framework aims to determine the optimized acquisition scheme (OAS) with a data-driven procedure minimizing the squared error of model-estimated parameters. We tested the proposed method over five heterogeneous DWI models exploiting both low and high b-values (i.e., diffusion tensor imaging [DTI], free water, intra-voxel incoherent motion [IVIM], diffusion kurtosis imaging [DKI], and neurite orientation dispersion and density imaging [NODDI]). A voxel-level and region of interest (ROI)-level analysis was conducted over the white matter and in 48 fiber bundles, respectively. Results showed that acquiring data for the five abovementioned models via OAS requires 14 min, compared with 35 min for the joint recommended acquisition protocol. The parameters derived from the reference acquisition scheme and the OAS are comparable in terms of estimated values, noise, and tissue contrast. Furthermore, the power analysis showed that the OAS retains the potential sensitivity to group-level differences in the parameters of interest, with the exception of the free water model. Overall, there is a linear correspondence (R2 = 0.91) between OAS and reference-derived parameters. In conclusion, the proposed framework optimizes the shell acquisition scheme for a given set of DWI models (i.e., DTI, free water, IVIM, DKI, and NODDI), combining low and high b-values while saving acquisition time.
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Affiliation(s)
- Tommaso Ciceri
- Neuroimaging Unit, Scientific Institute IRCCS Eugenio Medea, Bosisio Parini, Italy
- Department of Information Engineering, University of Padua, Padua, Italy
| | - Alberto De Luca
- Image Sciences Institute, Division Imaging and Oncology, UMC Utrecht, Utrecht, The Netherlands
- Neurology Department, UMC Utrecht Brain Center, UMC Utrecht, Utrecht, The Netherlands
| | - Nivedita Agarwal
- Diagnostic Imaging and Neuroradiology Unit, Scientific Institute IRCCS Eugenio Medea, Bosisio Parini, Italy
| | - Filippo Arrigoni
- Pediatric Radiology and Neuroradiology Department, V. Buzzi Children's Hospital, Milan, Italy
| | - Denis Peruzzo
- Neuroimaging Unit, Scientific Institute IRCCS Eugenio Medea, Bosisio Parini, Italy
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25
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Vilela-Filho O, Freitas ELA, Goulart LC, Lino-Filho AM, Carneiro R, Fernandes-Santos B. 7T Magnetic Resonance Imaging Probabilistic Tractography-Based Evidence of Decussation of the Fibers Between the Lateral Geniculate Nucleus and the Primary Visual Area. World Neurosurg 2024; 188:e555-e560. [PMID: 38823444 DOI: 10.1016/j.wneu.2024.05.152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 05/26/2024] [Accepted: 05/26/2024] [Indexed: 06/03/2024]
Abstract
BACKGROUND Geniculocalcarine fibers are thought to be exclusively ipsilateral. However, recent findings challenged this belief, revealing bilateral recruiting responses in occipitotemporoparietal regions upon unilateral stimulation of the lateral geniculate nucleus (LGN) in humans. This raised the intriguing possibility of bilateral projections to primary visual areas (V1). This study sought to explore the hypothetical decussation of the geniculocalcarine tract. METHODS 40 healthy individuals' 7T magnetic resonance images from the Human Connectome Project were examined. Employing MRtrix3 software with the constrained spherical deconvolution algorithm, scans were processed. LGN served as the seed region and contralateral regions of interest (splenium of the corpus callosum, posterior commissure, LGN, V1, pulvinar, and superior colliculus) were defined to reconstruct the hypothetical decussated fibers. Tractography included contralateral V1 as the target region in all segmentations, excluding ipsilateral V1 to eliminate fibers leading to or originating from this area. Additionally, a segmentation of the tract originating from LGN and projecting to the ipsilateral V1 was performed. Mean fraction anisotropy and mean diffusivity metrics were extracted from the density maps. RESULTS Observations revealed a substantial volume of decussated fibers between LGN and contralateral V1 via the splenium of the corpus callosum, albeit much smaller than ipsilateral fibers. The volume of ipsilateral fibers was similar in both sides. Left LGN-originating decussated fibers were more than double those originating from the right LGN. Tract segmentation to other regions of interests yielded no fibers. CONCLUSIONS This study suggests a partial decussation of the fibers between LGN and V1, likely constituting the geniculocalcarine tract.
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Affiliation(s)
- Osvaldo Vilela-Filho
- Division of Neurosurgery, Department of Surgery, Medical School, Federal University of Goiás, Goiânia, Brazil; Department of Neurosurgery, Clinics Hospital, Federal University of Goiás, Goiânia, Brazil.
| | - Erom L A Freitas
- Department of Medicine, Federal University of Sergipe, Aracaju, Brazil
| | - Lissa C Goulart
- Department of Neurosurgery, Clinics Hospital, Federal University of Goiás, Goiânia, Brazil
| | - Adriano M Lino-Filho
- Department of Neurosurgery, Clinics Hospital, Federal University of Goiás, Goiânia, Brazil
| | - Rubens Carneiro
- Department of Radiology, Medical School, Federal University of Goiás, Goiânia, Brazil
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26
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Obaid S, Guberman GI, St-Onge E, Campbell E, Edde M, Lamsam L, Bouthillier A, Weil AG, Daducci A, Rheault F, Nguyen DK, Descoteaux M. Progressive remodeling of structural networks following surgery for operculo-insular epilepsy. Front Neurol 2024; 15:1400601. [PMID: 39144703 PMCID: PMC11322451 DOI: 10.3389/fneur.2024.1400601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 07/15/2024] [Indexed: 08/16/2024] Open
Abstract
Introduction Operculo-insular epilepsy (OIE) is a rare condition amenable to surgery in well-selected cases. Despite the high rate of neurological complications associated with OIE surgery, most postoperative deficits recover fully and rapidly. We provide insights into this peculiar pattern of functional recovery by investigating the longitudinal reorganization of structural networks after surgery for OIE in 10 patients. Methods Structural T1 and diffusion-weighted MRIs were performed before surgery (t0) and at 6 months (t1) and 12 months (t2) postoperatively. These images were processed with an original, comprehensive structural connectivity pipeline. Using our method, we performed comparisons between the t0 and t1 timepoints and between the t1 and t2 timepoints to characterize the progressive structural remodeling. Results We found a widespread pattern of postoperative changes primarily in the surgical hemisphere, most of which consisted of reductions in connectivity strength (CS) and regional graph theoretic measures (rGTM) that reflect local connectivity. We also observed increases in CS and rGTMs predominantly in regions located near the resection cavity and in the contralateral healthy hemisphere. Finally, most structural changes arose in the first six months following surgery (i.e., between t0 and t1). Discussion To our knowledge, this study provides the first description of postoperative structural connectivity changes following surgery for OIE. The ipsilateral reductions in connectivity unveiled by our analysis may result from the reversal of seizure-related structural alterations following postoperative seizure control. Moreover, the strengthening of connections in peri-resection areas and in the contralateral hemisphere may be compatible with compensatory structural plasticity, a process that could contribute to the recovery of functions seen following operculo-insular resections for focal epilepsy.
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Affiliation(s)
- Sami Obaid
- Department of Neurosciences, University of Montreal, Montreal, QC, Canada
- University of Montreal Hospital Research Center (CRCHUM), Montreal, QC, Canada
- Division of Neurosurgery, Department of Surgery, University of Montreal Hospital Center (CHUM), Montreal, QC, Canada
- Sherbrooke Connectivity Imaging Lab (SCIL), Sherbrooke University, Sherbrooke, QC, Canada
| | - Guido I. Guberman
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Etienne St-Onge
- Department of Computer Science and Engineering, Université du Québec en Outaouais, Montreal, QC, Canada
| | - Emma Campbell
- Department of Psychology, University of Montreal, Montreal, QC, Canada
| | - Manon Edde
- Sherbrooke Connectivity Imaging Lab (SCIL), Sherbrooke University, Sherbrooke, QC, Canada
| | - Layton Lamsam
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, United States
| | - Alain Bouthillier
- Division of Neurosurgery, Department of Surgery, University of Montreal Hospital Center (CHUM), Montreal, QC, Canada
| | - Alexander G. Weil
- Department of Neurosciences, University of Montreal, Montreal, QC, Canada
- Division of Pediatric Neurosurgery, Department of Surgery, Sainte Justine Hospital, University of Montreal, Montreal, QC, Canada
| | | | - François Rheault
- Medical Imaging and Neuroimaging (MINi) Lab, Sherbrooke University, Sherbrooke, QC, Canada
| | - Dang K. Nguyen
- Department of Neurosciences, University of Montreal, Montreal, QC, Canada
- University of Montreal Hospital Research Center (CRCHUM), Montreal, QC, Canada
- Division of Neurology, University of Montreal Hospital Center (CHUM), Montreal, QC, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab (SCIL), Sherbrooke University, Sherbrooke, QC, Canada
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27
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Bertò G, Rooks LT, Broglio SP, McAllister TA, McCrea MA, Pasquina PF, Giza C, Brooks A, Mihalik J, Guskiewicz K, Goldman J, Duma S, Rowson S, Port NL, Pestilli F. Diffusion tensor analysis of white matter tracts is prognostic of persisting post-concussion symptoms in collegiate athletes. Neuroimage Clin 2024; 43:103646. [PMID: 39106542 PMCID: PMC11347060 DOI: 10.1016/j.nicl.2024.103646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 06/15/2024] [Accepted: 07/19/2024] [Indexed: 08/09/2024]
Abstract
BACKGROUND AND OBJECTIVES After a concussion diagnosis, the most important issue for patients and loved ones is how long it will take them to recover. The main objective of this study is to develop a prognostic model of concussion recovery. This model would benefit many patients worldwide, allowing for early treatment intervention. METHODS The Concussion Assessment, Research and Education (CARE) consortium study enrolled collegiate athletes from 30 sites (NCAA athletic departments and US Department of Defense service academies), 4 of which participated in the Advanced Research Core, which included diffusion-weighted MRI (dMRI) data collection. We analyzed the dMRI data of 51 injuries of concussed athletes scanned within 48 h of injury. All athletes were cleared to return-to-play by the local medical staff following a standardized, graduated protocol. The primary outcome measure is days to clearance of unrestricted return-to-play. Injuries were divided into early (return-to-play < 28 days) and late (return-to-play >= 28 days) recovery based on the return-to-play clinical records. The late recovery group meets the standard definition of Persisting Post-Concussion Symptoms (PPCS). Data were processed using automated, state-of-the-art, rigorous methods for reproducible data processing using brainlife.io. All processed data derivatives are made available at https://brainlife.io/project/63b2ecb0daffe2c2407ee3c5/dataset. The microstructural properties of 47 major white matter tracts, 5 callosal, 15 subcortical, and 148 cortical structures were mapped. Fractional Anisotropy (FA) and Mean Diffusivity (MD) were estimated for each tract and structure. Correlation analysis and Receiver Operator Characteristic (ROC) analysis were then performed to assess the association between the microstructural properties and return-to-play. Finally, a Logistic Regression binary classifier (LR-BC) was used to classify the injuries between the two recovery groups. RESULTS The mean FA across all white matter volume was negatively correlated with return-to-play (r = -0.38, p = 0.00001). No significant association between mean MD and return-to-play was found, neither for FA nor MD for any other structure. The mean FA of 47 white matter tracts was negatively correlated with return-to-play (rμ = -0.27; rσ = 0.08; rmin = -0.1; rmax = -0.43). Across all tracts, a large mean ROC Area Under the Curve (AUCFA) of 0.71 ± 0.09 SD was found. The top classification performance of the LR-BC was AUC = 0.90 obtained using the 16 statistically significant white matter tracts. DISCUSSION Utilizing a free, open-source, and automated cloud-based neuroimaging pipeline and app (https://brainlife.io/docs/tutorial/using-clairvoy/), a prognostic model has been developed, which predicts athletes at risk for slow recovery (PPCS) with an AUC=0.90, balanced accuracy = 0.89, sensitivity = 1.0, and specificity = 0.79. The small number of participants in this study (51 injuries) is a significant limitation and supports the need for future large concussion dMRI studies and focused on recovery.
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Affiliation(s)
- Giulia Bertò
- Department of Psychology and Department of Neuroscience, Center for Perceptual Systems, Center for Learning and Memory, The University of Texas at Austin, Austin, TX, USA
| | - Lauren T Rooks
- Indiana University School of Optometry and Program in Neuroscience, Indiana University, Bloomington IN, USA
| | - Steven P Broglio
- Michigan Concussion Center, University of Michigan, Ann Arbor, MI, USA
| | | | - Michael A McCrea
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Paul F Pasquina
- Department of Physical Medicine and Rehabilitation at the Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Christopher Giza
- Pediatric Neurology, University of California, Los Angeles, CA, USA
| | - Alison Brooks
- Department of Orthopaedics and Rehabilitation, University of Wisconsin Madison, Madison WI, USA
| | - Jason Mihalik
- Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kevin Guskiewicz
- Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Josh Goldman
- Family Medicine & Sports Medicine, UCLA Medical School, Los Angeles, CA, USA
| | - Stefan Duma
- Departmentl of Biomedical Engineering & Mechanics, Virginia Tech, Blacksburg, VA, USA
| | - Steven Rowson
- Departmentl of Biomedical Engineering & Mechanics, Virginia Tech, Blacksburg, VA, USA
| | - Nicholas L Port
- Indiana University School of Optometry and Program in Neuroscience, Indiana University, Bloomington IN, USA.
| | - Franco Pestilli
- Department of Psychology and Department of Neuroscience, Center for Perceptual Systems, Center for Learning and Memory, The University of Texas at Austin, Austin, TX, USA.
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Matthews TE, Lumaca M, Witek MAG, Penhune VB, Vuust P. Music reward sensitivity is associated with greater information transfer capacity within dorsal and motor white matter networks in musicians. Brain Struct Funct 2024:10.1007/s00429-024-02836-x. [PMID: 39052097 DOI: 10.1007/s00429-024-02836-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Accepted: 07/12/2024] [Indexed: 07/27/2024]
Abstract
There are pronounced differences in the degree to which individuals experience music-induced pleasure which are linked to variations in structural connectivity between auditory and reward areas. However, previous studies exploring the link between white matter structure and music reward sensitivity (MRS) have relied on standard diffusion tensor imaging methods, which present challenges in terms of anatomical accuracy and interpretability. Further, the link between MRS and connectivity in regions outside of auditory-reward networks, as well as the role of musical training, have yet to be investigated. Therefore, we investigated the relation between MRS and structural connectivity in a large number of directly segmented and anatomically verified white matter tracts in musicians (n = 24) and non-musicians (n = 23) using state-of-the-art tract reconstruction and fixel-based analysis. Using a manual tract-of-interest approach, we additionally tested MRS-white matter associations in auditory-reward networks seen in previous studies. Within the musician group, there was a significant positive relation between MRS and fiber density and cross section in the right middle longitudinal fascicle connecting auditory and inferior parietal cortices. There were also positive relations between MRS and fiber-bundle cross-section in tracts connecting the left thalamus to the ventral precentral gyrus and connecting the right thalamus to the right supplementary motor area, however, these did not survive FDR correction. These results suggest that, within musicians, dorsal auditory and motor networks are crucial to MRS, possibly via their roles in top-down predictive processing and auditory-motor transformations.
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Affiliation(s)
- Tomas E Matthews
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University Hospital, Nørrebrogade 44, Building 1A, Aarhus C, 8000, Denmark.
| | - Massimo Lumaca
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University Hospital, Nørrebrogade 44, Building 1A, Aarhus C, 8000, Denmark
| | - Maria A G Witek
- Department of Music School of Languages, Art History and Music, University of Birmingham, Cultures, Birmingham, B15 2TT, UK
| | - Virginia B Penhune
- Department of Psychology, Concordia University, 7141 Sherbrooke St W, Montreal, QC, H4B 1R6, Canada
| | - Peter Vuust
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University Hospital, Nørrebrogade 44, Building 1A, Aarhus C, 8000, Denmark
- Royal Academy of Music, Skovgaardsgade 2C, Aarhus C, DK-8000, Denmark
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29
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Calixto C, Soldatelli MD, Li B, Pierotich L, Gholipour A, Warfield SK, Karimi D. White matter tract crossing and bottleneck regions in the fetal brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.20.603804. [PMID: 39091823 PMCID: PMC11291018 DOI: 10.1101/2024.07.20.603804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
There is a growing interest in using diffusion MRI to study the white matter tracts and structural connectivity of the fetal brain. Recent progress in data acquisition and processing suggests that this imaging modality has a unique role in elucidating the normal and abnormal patterns of neurodevelopment in utero. However, there have been no efforts to quantify the prevalence of crossing tracts and bottleneck regions, important issues that have been extensively researched for adult brains. In this work, we determined the brain regions with crossing tracts and bottlenecks between 23 and 36 gestational weeks. We performed probabilistic tractography on 59 fetal brain scans and extracted a set of 51 distinct white tracts, which we grouped into 10 major tract bundle groups. We analyzed the results to determine the patterns of tract crossings and bottlenecks. Our results showed that 20-25% of the white matter voxels included two or three crossing tracts. Bottlenecks were more prevalent. Between 75-80% of the voxels were characterized as bottlenecks, with more than 40% of the voxels involving four or more tracts. The results of this study highlight the challenge of fetal brain tractography and structural connectivity assessment and call for innovative image acquisition and analysis methods to mitigate these problems.
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Affiliation(s)
- Camilo Calixto
- Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Matheus D Soldatelli
- Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Bo Li
- Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Lana Pierotich
- Department of Pediatrics, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Ali Gholipour
- Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Simon K Warfield
- Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Davood Karimi
- Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
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Chen R, Zhao R, Li H, Xu X, Li M, Zhao Z, Sun C, Wang G, Wu D. Development of the Fetal Brain Corticocortical Structural Network during the Second-to-Third Trimester Based on Diffusion MRI. J Neurosci 2024; 44:e1567232024. [PMID: 38844343 PMCID: PMC11255424 DOI: 10.1523/jneurosci.1567-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 05/08/2024] [Accepted: 05/31/2024] [Indexed: 07/19/2024] Open
Abstract
During the second-to-third trimester, the neuronal pathways of the fetal brain experience rapid development, resulting in the complex architecture of the interwired network at birth. While diffusion MRI-based tractography has been employed to study the prenatal development of structural connectivity network (SCN) in preterm neonatal and postmortem fetal brains, the in utero development of SCN in the normal fetal brain remains largely unknown. In this study, we utilized in utero dMRI data from human fetuses of both sexes between 26 and 38 gestational weeks to investigate the developmental trajectories of the fetal brain SCN, focusing on intrahemispheric connections. Our analysis revealed significant increases in global efficiency, mean local efficiency, and clustering coefficient, along with significant decrease in shortest path length, while small-worldness persisted during the studied period, revealing balanced network integration and segregation. Widespread short-ranged connectivity strengthened significantly. The nodal strength developed in a posterior-to-anterior and medial-to-lateral order, reflecting a spatiotemporal gradient in cortical network connectivity development. Moreover, we observed distinct lateralization patterns in the fetal brain SCN. Globally, there was a leftward lateralization in network efficiency, clustering coefficient, and small-worldness. The regional lateralization patterns in most language, motor, and visual-related areas were consistent with prior knowledge, except for Wernicke's area, indicating lateralized brain wiring is an innate property of the human brain starting from the fetal period. Our findings provided a comprehensive view of the development of the fetal brain SCN and its lateralization, as a normative template that may be used to characterize atypical development.
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Affiliation(s)
- Ruike Chen
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, P. R. China
| | - Ruoke Zhao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, P. R. China
| | - Haotian Li
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, P. R. China
| | - Xinyi Xu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, P. R. China
| | - Mingyang Li
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, P. R. China
| | - Zhiyong Zhao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, P. R. China
| | - Cong Sun
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, P. R. China
| | - Guangbin Wang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, P. R. China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, P. R. China
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31
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Tanner J, Faskowitz J, Teixeira AS, Seguin C, Coletta L, Gozzi A, Mišić B, Betzel RF. A multi-modal, asymmetric, weighted, and signed description of anatomical connectivity. Nat Commun 2024; 15:5865. [PMID: 38997282 PMCID: PMC11245624 DOI: 10.1038/s41467-024-50248-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 07/01/2024] [Indexed: 07/14/2024] Open
Abstract
The macroscale connectome is the network of physical, white-matter tracts between brain areas. The connections are generally weighted and their values interpreted as measures of communication efficacy. In most applications, weights are either assigned based on imaging features-e.g. diffusion parameters-or inferred using statistical models. In reality, the ground-truth weights are unknown, motivating the exploration of alternative edge weighting schemes. Here, we explore a multi-modal, regression-based model that endows reconstructed fiber tracts with directed and signed weights. We find that the model fits observed data well, outperforming a suite of null models. The estimated weights are subject-specific and highly reliable, even when fit using relatively few training samples, and the networks maintain a number of desirable features. In summary, we offer a simple framework for weighting connectome data, demonstrating both its ease of implementation while benchmarking its utility for typical connectome analyses, including graph theoretic modeling and brain-behavior associations.
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Affiliation(s)
- Jacob Tanner
- Cognitive Science Program, Indiana University, Bloomington, IN, USA
- School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA
| | - Joshua Faskowitz
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Andreia Sofia Teixeira
- LASIGE, Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - Caio Seguin
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | | | - Alessandro Gozzi
- Functional Neuroimaging Lab, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, Rovereto, Italy
| | - Bratislav Mišić
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Richard F Betzel
- Cognitive Science Program, Indiana University, Bloomington, IN, USA.
- School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA.
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA.
- Program in Neuroscience, Indiana University, Bloomington, IN, USA.
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32
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Kang X, Yoon BC, Grossner E, Adamson MM. Characteristics of the Structural Connectivity in Patients with Brain Injury and Chronic Health Symptoms: A Pilot Study. Neuroinformatics 2024:10.1007/s12021-024-09681-7. [PMID: 38990502 DOI: 10.1007/s12021-024-09681-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/03/2024] [Indexed: 07/12/2024]
Abstract
Diffusion properties from diffusion tensor imaging (DTI) are exquisitely sensitive to white matter abnormalities incurred during traumatic brain injury (TBI), especially for those patients with chronic post-TBI symptoms such as headaches, dizziness, fatigue, etc. The evaluation of structural and functional connectivity using DTI has become a promising method for identifying subtle alterations in brain connectivity associated with TBI that are otherwise not visible with conventional imaging. This study assessed whether TBI patients with (n = 17) or without (n = 16) chronic symptoms (TBIcs/TBIncs) exhibit any changes in structural connectivity (SC) and mean fractional anisotropy (mFA) of intra- and inter-hemispheric connections when compared to a control group (CG) (n = 13). Reductions in SC and mFA were observed for TBIcs compared to CG, but not for TBIncs. More connections were found to have mFA reductions than SC reductions. On the whole, SC is dominated by ipsilateral connections for all the groups after the comparison of contralateral and ipsilateral connections. More contra-ipsi reductions of mFA were found for TBIcs than TBIncs compared to CG. These findings suggest that TBI patients with chronic symptoms not only demonstrate decreased global and regional mFA but also reduced structural network connectivity.
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Affiliation(s)
- Xiaojian Kang
- WRIISC-Women, VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, 94304, USA.
- Rehabilitation Service, VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, 94304, USA.
| | - Byung C Yoon
- Department of Radiology, Stanford University School of Medicine, VA Palo Alto Heath Care System, Palo Alto, CA, 94304, USA
| | - Emily Grossner
- Department of Psychology, VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, 94304, USA
| | - Maheen M Adamson
- WRIISC-Women, VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, 94304, USA
- Rehabilitation Service, VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, 94304, USA
- Department of Neurosurgery, Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA, 94305, USA
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33
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Zanchi P, Mullier E, Fornari E, Guerrier de Dumast P, Alemán-Gómez Y, Ledoux JB, Beaty R, Hagmann P, Denervaud S. Differences in spatiotemporal brain network dynamics of Montessori and traditionally schooled students. NPJ SCIENCE OF LEARNING 2024; 9:45. [PMID: 38987286 PMCID: PMC11236971 DOI: 10.1038/s41539-024-00254-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 06/12/2024] [Indexed: 07/12/2024]
Abstract
Across development, experience has a strong impact on the way we think and adapt. School experience affects academic and social-emotional outcomes, yet whether differences in pedagogical experience modulate underlying brain network development is still unknown. In this study, we compared the brain network dynamics of students with different pedagogical backgrounds. Specifically, we characterized the diversity and stability of brain activity at rest by combining both resting-state fMRI and diffusion-weighted structural imaging data of 87 4-18 years old students experiencing either the Montessori pedagogy (i.e., student-led, trial-and-error pedagogy) or the traditional pedagogy (i.e., teacher-led, test-based pedagogy). Our results revealed spatiotemporal brain dynamics differences between students as a function of schooling experience at the whole-brain level. Students from Montessori schools showed overall higher functional integration (higher system diversity) and neural stability (lower spatiotemporal diversity) compared to traditionally schooled students. Higher integration was explained mainly through the cerebellar (CBL) functional network. In contrast, higher temporal stability was observed in the ventral attention, dorsal attention, somatomotor, frontoparietal, and CBL functional networks. This study suggests a form of experience-dependent dynamic functional connectivity plasticity, in learning-related networks.
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Affiliation(s)
- Paola Zanchi
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
| | - Emeline Mullier
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
| | - Eleonora Fornari
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
| | - Priscille Guerrier de Dumast
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
| | - Yasser Alemán-Gómez
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
| | - Jean-Baptiste Ledoux
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
| | - Roger Beaty
- Department of Psychology, Pennsylvania State University, University Park, TX, USA
| | - Patric Hagmann
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
| | - Solange Denervaud
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland.
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland.
- MRI Animal imaging and technology, Polytechnical School of Lausanne, Swiss Federal Institute of Technology Lausanne (EPFL), 1015, Lausanne, Switzerland.
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34
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Penas DR, Hashemi M, Jirsa VK, Banga JR. Parameter estimation in a whole-brain network model of epilepsy: Comparison of parallel global optimization solvers. PLoS Comput Biol 2024; 20:e1011642. [PMID: 38990984 PMCID: PMC11265693 DOI: 10.1371/journal.pcbi.1011642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 07/23/2024] [Accepted: 06/18/2024] [Indexed: 07/13/2024] Open
Abstract
The Virtual Epileptic Patient (VEP) refers to a computer-based representation of a patient with epilepsy that combines personalized anatomical data with dynamical models of abnormal brain activities. It is capable of generating spatio-temporal seizure patterns that resemble those recorded with invasive methods such as stereoelectro EEG data, allowing for the evaluation of clinical hypotheses before planning surgery. This study highlights the effectiveness of calibrating VEP models using a global optimization approach. The approach utilizes SaCeSS, a cooperative metaheuristic algorithm capable of parallel computation, to yield high-quality solutions without requiring excessive computational time. Through extensive benchmarking on synthetic data, our proposal successfully solved a set of different configurations of VEP models, demonstrating better scalability and superior performance against other parallel solvers. These results were further enhanced using a Bayesian optimization framework for hyperparameter tuning, with significant gains in terms of both accuracy and computational cost. Additionally, we added a scalable uncertainty quantification phase after model calibration, and used it to assess the variability in estimated parameters across different problems. Overall, this study has the potential to improve the estimation of pathological brain areas in drug-resistant epilepsy, thereby to inform the clinical decision-making process.
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Affiliation(s)
- David R. Penas
- Computational Biology Lab, MBG-CSIC (Spanish National Research Council), Pontevedra, Spain
| | - Meysam Hashemi
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Viktor K. Jirsa
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Julio R. Banga
- Computational Biology Lab, MBG-CSIC (Spanish National Research Council), Pontevedra, Spain
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35
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Takemura H, Kruper JA, Miyata T, Rokem A. Tractometry of Human Visual White Matter Pathways in Health and Disease. Magn Reson Med Sci 2024; 23:316-340. [PMID: 38866532 PMCID: PMC11234945 DOI: 10.2463/mrms.rev.2024-0007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2024] Open
Abstract
Diffusion-weighted MRI (dMRI) provides a unique non-invasive view of human brain tissue properties. The present review article focuses on tractometry analysis methods that use dMRI to assess the properties of brain tissue within the long-range connections comprising brain networks. We focus specifically on the major white matter tracts that convey visual information. These connections are particularly important because vision provides rich information from the environment that supports a large range of daily life activities. Many of the diseases of the visual system are associated with advanced aging, and tractometry of the visual system is particularly important in the modern aging society. We provide an overview of the tractometry analysis pipeline, which includes a primer on dMRI data acquisition, voxelwise model fitting, tractography, recognition of white matter tracts, and calculation of tract tissue property profiles. We then review dMRI-based methods for analyzing visual white matter tracts: the optic nerve, optic tract, optic radiation, forceps major, and vertical occipital fasciculus. For each tract, we review background anatomical knowledge together with recent findings in tractometry studies on these tracts and their properties in relation to visual function and disease. Overall, we find that measurements of the brain's visual white matter are sensitive to a range of disorders and correlate with perceptual abilities. We highlight new and promising analysis methods, as well as some of the current barriers to progress toward integration of these methods into clinical practice. These barriers, such as variability in measurements between protocols and instruments, are targets for future development.
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Affiliation(s)
- Hiromasa Takemura
- Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki, Aichi, Japan
- Graduate Institute for Advanced Studies, SOKENDAI, Hayama, Kanagawa, Japan
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Osaka, Japan
| | - John A Kruper
- Department of Psychology and eScience Institute, University of Washington, Seattle, WA, USA
| | - Toshikazu Miyata
- Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki, Aichi, Japan
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Osaka, Japan
| | - Ariel Rokem
- Department of Psychology and eScience Institute, University of Washington, Seattle, WA, USA
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Behroozi M, Graïc JM, Gerussi T. Beyond the surface: how ex-vivo diffusion-weighted imaging reveals large animal brain microstructure and connectivity. Front Neurosci 2024; 18:1411982. [PMID: 38988768 PMCID: PMC11233460 DOI: 10.3389/fnins.2024.1411982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Accepted: 06/12/2024] [Indexed: 07/12/2024] Open
Abstract
Diffusion-weighted Imaging (DWI) is an effective and state-of-the-art neuroimaging method that non-invasively reveals the microstructure and connectivity of tissues. Recently, novel applications of the DWI technique in studying large brains through ex-vivo imaging enabled researchers to gain insights into the complex neural architecture in different species such as those of Perissodactyla (e.g., horses and rhinos), Artiodactyla (e.g., bovids, swines, and cetaceans), and Carnivora (e.g., felids, canids, and pinnipeds). Classical in-vivo tract-tracing methods are usually considered unsuitable for ethical and practical reasons, in large animals or protected species. Ex-vivo DWI-based tractography offers the chance to examine the microstructure and connectivity of formalin-fixed tissues with scan times and precision that is not feasible in-vivo. This paper explores DWI's application to ex-vivo brains of large animals, highlighting the unique insights it offers into the structure of sometimes phylogenetically different neural networks, the connectivity of white matter tracts, and comparative evolutionary adaptations. Here, we also summarize the challenges, concerns, and perspectives of ex-vivo DWI that will shape the future of the field in large brains.
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Affiliation(s)
- Mehdi Behroozi
- Department of Biopsychology, Faculty of Psychology, Institute of Cognitive Neuroscience, Ruhr-University Bochum, Bochum, Germany
| | - Jean-Marie Graïc
- Department of Comparative Biomedicine and Food Science (BCA), University of Padova, Legnaro, Italy
| | - Tommaso Gerussi
- Department of Comparative Biomedicine and Food Science (BCA), University of Padova, Legnaro, Italy
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, Hong Kong SAR, China
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37
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Vinci-Booher S, McDonald DJ, Berquist E, Pestilli F. Associative white matter tracts selectively predict sensorimotor learning. Commun Biol 2024; 7:762. [PMID: 38909103 PMCID: PMC11193801 DOI: 10.1038/s42003-024-06420-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 06/06/2024] [Indexed: 06/24/2024] Open
Abstract
Human learning varies greatly among individuals and is related to the microstructure of major white matter tracts in several learning domains, yet the impact of the existing microstructure of white matter tracts on future learning outcomes remains unclear. We employed a machine-learning model selection framework to evaluate whether existing microstructure might predict individual differences in learning a sensorimotor task, and further, if the mapping between tract microstructure and learning was selective for learning outcomes. We used diffusion tractography to measure the mean fractional anisotropy (FA) of white matter tracts in 60 adult participants who then practiced drawing a set of 40 unfamiliar symbols repeatedly using a digital writing tablet. We measured drawing learning as the slope of draw duration over the practice session and measured visual recognition learning for the symbols using an old/new 2-AFC task. Results demonstrated that tract microstructure selectively predicted learning outcomes, with left hemisphere pArc and SLF3 tracts predicting drawing learning and the left hemisphere MDLFspl predicting visual recognition learning. These results were replicated using repeat, held-out data and supported with complementary analyses. Results suggest that individual differences in the microstructure of human white matter tracts may be selectively related to future learning outcomes.
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Affiliation(s)
- S Vinci-Booher
- Department of Psychological and Brain Sciences, Program for Neuroscience, Indiana University, Bloomington, IN, USA
- Department of Psychology and Human Development, Vanderbilt University, Nashville, TN, USA
| | - D J McDonald
- Department of Statistics, University of British Columbia, Vancouver, BC, Canada
| | - E Berquist
- Department of Psychological and Brain Sciences, Program for Neuroscience, Indiana University, Bloomington, IN, USA
| | - F Pestilli
- Department of Psychological and Brain Sciences, Program for Neuroscience, Indiana University, Bloomington, IN, USA.
- Department of Psychology, Center for Perceptual Systems, Center for Theoretical and Computational Neuroscience, Center for Aging Populations Sciences, Center for Learning and Memory, University of Texas at Austin, Austin, TX, USA.
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38
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Lautarescu A, Bonthrone AF, Bos B, Barratt B, Counsell SJ. Advances in fetal and neonatal neuroimaging and everyday exposures. Pediatr Res 2024:10.1038/s41390-024-03294-1. [PMID: 38877283 DOI: 10.1038/s41390-024-03294-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 04/25/2024] [Accepted: 04/29/2024] [Indexed: 06/16/2024]
Abstract
The complex, tightly regulated process of prenatal brain development may be adversely affected by "everyday exposures" such as stress and environmental pollutants. Researchers are only just beginning to understand the neural sequelae of such exposures, with advances in fetal and neonatal neuroimaging elucidating structural, microstructural, and functional correlates in the developing brain. This narrative review discusses the wide-ranging literature investigating the influence of parental stress on fetal and neonatal brain development as well as emerging literature assessing the impact of exposure to environmental toxicants such as lead and air pollution. These 'everyday exposures' can co-occur with other stressors such as social and financial deprivation, and therefore we include a brief discussion of neuroimaging studies assessing the effect of social disadvantage. Increased exposure to prenatal stressors is associated with alterations in the brain structure, microstructure and function, with some evidence these associations are moderated by factors such as infant sex. However, most studies examine only single exposures and the literature on the relationship between in utero exposure to pollutants and fetal or neonatal brain development is sparse. Large cohort studies are required that include evaluation of multiple co-occurring exposures in order to fully characterize their impact on early brain development. IMPACT: Increased prenatal exposure to parental stress and is associated with altered functional, macro and microstructural fetal and neonatal brain development. Exposure to air pollution and lead may also alter brain development in the fetal and neonatal period. Further research is needed to investigate the effect of multiple co-occurring exposures, including stress, environmental toxicants, and socioeconomic deprivation on early brain development.
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Affiliation(s)
- Alexandra Lautarescu
- Department of Perinatal Imaging and Health, Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Alexandra F Bonthrone
- Department of Perinatal Imaging and Health, Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Brendan Bos
- MRC Centre for Environment and Health, Imperial College London, London, UK
| | - Ben Barratt
- MRC Centre for Environment and Health, Imperial College London, London, UK
| | - Serena J Counsell
- Department of Perinatal Imaging and Health, Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
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Wende T, Güresir E, Wach J, Vychopen M, Hoffmann A, Prasse G, Wilhelmy F, Kasper J. Radiomic white matter parameters of functional integrity of the corticospinal tract in high-grade glioma. Sci Rep 2024; 14:12891. [PMID: 38839940 PMCID: PMC11153211 DOI: 10.1038/s41598-024-63813-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Accepted: 06/03/2024] [Indexed: 06/07/2024] Open
Abstract
Tractography has become a widely available tool for the planning of neurosurgical operations as well as for neuroscientific research. The absence of patient interaction makes it easily applicable. However, it leaves uncertainty about the functional relevance of the identified bundles. We retrospectively analyzed the correlation of white matter markers with their clinical function in 24 right-handed patients who underwent first surgery for high-grade glioma. Morphological affection of the corticospinal tract (CST) and grade of paresis were assessed before surgery. Tractography was performed manually with MRTrix3 and automatically with TractSeg. Median and mean fractional anisotropy (FA) from manual tractography showed a significant correlation with CST affection (p = 0.008) and paresis (p = 0.015, p = 0.026). CST affection correlated further most with energy, and surface-volume ratio (p = 0.014) from radiomic analysis. Paresis correlated most with maximum 2D column diameter (p = 0.005), minor axis length (p = 0.006), and kurtosis (p = 0.008) from radiomic analysis. Streamline count yielded no significant correlations. In conclusion, mean or median FA can be used for the assessment of CST integrity in high-grade glioma. Also, several radiomic parameters are suited to describe tract integrity and may be used to quantitatively analyze white matter in the future.
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Affiliation(s)
- Tim Wende
- Department of Neurosurgery, University Hospital Leipzig, Liebigstr. 20, 04103, Leipzig, Germany.
| | - Erdem Güresir
- Department of Neurosurgery, University Hospital Leipzig, Liebigstr. 20, 04103, Leipzig, Germany
| | - Johannes Wach
- Department of Neurosurgery, University Hospital Leipzig, Liebigstr. 20, 04103, Leipzig, Germany
| | - Martin Vychopen
- Department of Neurosurgery, University Hospital Leipzig, Liebigstr. 20, 04103, Leipzig, Germany
| | - Anastasia Hoffmann
- Department of Neurosurgery, University Hospital Leipzig, Liebigstr. 20, 04103, Leipzig, Germany
- Institute of Neuroradiology, University Hospital Leipzig, Leipzig, Germany
| | - Gordian Prasse
- Institute of Neuroradiology, University Hospital Leipzig, Leipzig, Germany
| | - Florian Wilhelmy
- Department of Neurosurgery, University Hospital Leipzig, Liebigstr. 20, 04103, Leipzig, Germany
| | - Johannes Kasper
- Department of Neurosurgery, University Hospital Leipzig, Liebigstr. 20, 04103, Leipzig, Germany
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Fiscone C, Sighinolfi G, Manners DN, Motta L, Venturi G, Panzera I, Zaccagna F, Rundo L, Lugaresi A, Lodi R, Tonon C, Castelli M. Multiparametric MRI dataset for susceptibility-based radiomic feature extraction and analysis. Sci Data 2024; 11:575. [PMID: 38834674 DOI: 10.1038/s41597-024-03418-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 05/24/2024] [Indexed: 06/06/2024] Open
Abstract
Multiple sclerosis (MS) is a progressive demyelinating disease impacting the central nervous system. Conventional Magnetic Resonance Imaging (MRI) techniques (e.g., T2w images) help diagnose MS, although they sometimes reveal non-specific lesions. Quantitative MRI techniques are capable of quantifying imaging biomarkers in vivo, offering the potential to identify specific signs related to pre-clinical inflammation. Among those techniques, Quantitative Susceptibility Mapping (QSM) is particularly useful for studying processes that influence the magnetic properties of brain tissue, such as alterations in myelin concentration. Because of its intrinsic quantitative nature, it is particularly well-suited to be analyzed through radiomics, including techniques that extract a high number of complex and multi-dimensional features from radiological images. The dataset presented in this work provides information about normal-appearing white matter (NAWM) in a cohort of MS patients and healthy controls. It includes QSM-based radiomic features from NAWM and its tracts, and MR sequences necessary to implement the pipeline: T1w, T2w, QSM, DWI. The workflow is outlined in this article, along with an application showing feature reliability assessment.
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Affiliation(s)
- Cristiana Fiscone
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Giovanni Sighinolfi
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - David Neil Manners
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
- Department for Life Quality Sciences, University of Bologna, Bologna, Italy.
| | - Lorenzo Motta
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Greta Venturi
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Ivan Panzera
- UOSI Riabilitazione Sclerosi Multipla, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Fulvio Zaccagna
- Department of Imaging, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
- Investigative Medicine Division, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Leonardo Rundo
- Department of Information and Electrical Engineering and Applied Mathematics, University of Salerno, Fisciano, Italy
| | - Alessandra Lugaresi
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
- UOSI Riabilitazione Sclerosi Multipla, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Raffaele Lodi
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Caterina Tonon
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Mauro Castelli
- NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa, Campus de Campolide, 1070-312, Lisbon, Portugal
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Midrigan-Ciochina L, Vodacek KP, Sewell C, Corina DP. A Comparison of White Matter Brain Differences in Monolingual and Highly Proficient Multilingual Speakers. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2024; 5:497-527. [PMID: 38911457 PMCID: PMC11192512 DOI: 10.1162/nol_a_00144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 03/20/2024] [Indexed: 06/25/2024]
Abstract
Language processing relies on the communication between brain regions that is achieved through several white matter tracts, part of the dorsal, ventral, and medial pathways involved in language processing and control (Coggins et al., 2004; Friederici & Gierhan, 2013; Hickok & Poeppel, 2007; Luk et al., 2011). While changes in white matter tract morphology have been reported as a function of second language learning in bilinguals, little is known about changes that may be present in multilanguage users. Here we investigate white matter morphometry in a group of highly proficient multilinguals, (individuals with proficiency in four or more languages), compared to a group of monolinguals. White matter morphometry was quantified using a fixel-based analysis (Raffelt et al., 2015; Raffelt et al., 2017; Tournier et al., 2007). Higher fiber cross-section and lower fiber density values were observed for the multilinguals, in the dorsal pathways (superior longitudinal fasciculus and arcuate fasciculus) and the ventral pathway, including the inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, and the uncinate fasciculus. Segments of the corpus callosum, the fornix, and the cortico-spinal tract showed decreases in all three morphometry measures for multilinguals. The findings suggest differential efficiencies in neural communication between domain-specific language regions and domain-general cognitive processes underlying multilingual language use. We discuss the results in relation to the bilingual Anterior to Posterior and Subcortical Shift (BAPSS) hypothesis (Grundy et al., 2017) and the Dynamic Restructuring Model (Pliatsikas, 2020).
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Affiliation(s)
- Ludmila Midrigan-Ciochina
- Center for Mind and Brain, University of California, Davis, Davis, CA, USA
- Department of Linguistics and Human Ecology, University of California, Davis, Davis, CA, USA
| | - Kayla P. Vodacek
- Center for Mind and Brain, University of California, Davis, Davis, CA, USA
| | - Cristina Sewell
- Center for Mind and Brain, University of California, Davis, Davis, CA, USA
| | - David P. Corina
- Center for Mind and Brain, University of California, Davis, Davis, CA, USA
- Department of Linguistics and Psychology, University of California, Davis, Davis, CA, USA
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Weerasekera A, Ion-Mărgineanu A, Nolan GP, Mody M. Subcortical-cortical white matter connectivity in adults with autism spectrum disorder and schizophrenia patients. Psychiatry Res Neuroimaging 2024; 340:111806. [PMID: 38508025 DOI: 10.1016/j.pscychresns.2024.111806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 11/20/2023] [Accepted: 02/29/2024] [Indexed: 03/22/2024]
Abstract
Autism spectrum disorder (ASD) and schizophrenia (SZ) are neuropsychiatric disorders that overlap in symptoms associated with social-cognitive impairment. Alterations of the cingulate cortex, subcortical, medial-temporal, and orbitofrontal structures are frequently reported in both disorders. In this study, we examined white-matter connectivity between these structures in adults with ASD and SZ patients compared with their respective neurotypical controls and indirectly with each other, using probabilistic and local DTI tractography. This exploratory study utilized publicly available neuroimaging databases, of adults with ASD (ABIDE II; n = 28) and SZ (COBRE; n = 38), age-gender matched neurotypicals (NT) and associated phenotypic data. Tractography was performed using Freesurfer and MRtrix software, and diffusion metrics of white-matter tracts between cingulate-, orbitofrontal- cortices, subcortical structures, parahippocampal, entorhinal cortex were assessed. In ASD, atypical diffusivity parameters were found in the isthmus cingulate and parahippocampal connectivity to subcortical and rostral-anterior cingulate, which were also associated with IQ and social skills (SRS). In contrast, atypical diffusivity parameters were observed between the medial-orbitofrontal cortex and subcortical structures in SZ, and were associated with executive function (i.e., IQ, processing speed) and emotional regulation. Overall, the results suggest that defects in the isthmus cingulate, medial-orbitofrontal, and striato-limbic white matter connectivity may help unravel the neural underpinnings of executive and social-emotional dysfunction at the core of neuropsychiatric disorders.
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Affiliation(s)
- Akila Weerasekera
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115, USA.
| | - Adrian Ion-Mărgineanu
- ESAT - STADIUS, KU Leuven, Leuven. Belgium; Biomed Artificial Intelligence LLC, Bucharest, Romania
| | - Garry P Nolan
- Department of Microbiology & Immunology, Stanford University School of Medicine, United States
| | - Maria Mody
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115, USA
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Li Z, Li Z, Bilgic B, Lee H, Ying K, Huang SY, Liao H, Tian Q. DIMOND: DIffusion Model OptimizatioN with Deep Learning. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2307965. [PMID: 38634608 PMCID: PMC11200022 DOI: 10.1002/advs.202307965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 02/09/2024] [Indexed: 04/19/2024]
Abstract
Diffusion magnetic resonance imaging is an important tool for mapping tissue microstructure and structural connectivity non-invasively in the in vivo human brain. Numerous diffusion signal models are proposed to quantify microstructural properties. Nonetheless, accurate estimation of model parameters is computationally expensive and impeded by image noise. Supervised deep learning-based estimation approaches exhibit efficiency and superior performance but require additional training data and may be not generalizable. A new DIffusion Model OptimizatioN framework using physics-informed and self-supervised Deep learning entitled "DIMOND" is proposed to address this problem. DIMOND employs a neural network to map input image data to model parameters and optimizes the network by minimizing the difference between the input acquired data and synthetic data generated via the diffusion model parametrized by network outputs. DIMOND produces accurate diffusion tensor imaging results and is generalizable across subjects and datasets. Moreover, DIMOND outperforms conventional methods for fitting sophisticated microstructural models including the kurtosis and NODDI model. Importantly, DIMOND reduces NODDI model fitting time from hours to minutes, or seconds by leveraging transfer learning. In summary, the self-supervised manner, high efficacy, and efficiency of DIMOND increase the practical feasibility and adoption of microstructure and connectivity mapping in clinical and neuroscientific applications.
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Affiliation(s)
- Zihan Li
- School of Biomedical EngineeringTsinghua UniversityBeijing100084P. R. China
| | - Ziyu Li
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordOX3 9DUUK
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalCharlestownMA02129USA
- Harvard Medical SchoolBostonMA02129USA
| | - Hong‐Hsi Lee
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalCharlestownMA02129USA
- Harvard Medical SchoolBostonMA02129USA
| | - Kui Ying
- Department of Engineering PhysicsTsinghua UniversityBeijing100084P. R. China
| | - Susie Y. Huang
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalCharlestownMA02129USA
- Harvard Medical SchoolBostonMA02129USA
| | - Hongen Liao
- School of Biomedical EngineeringTsinghua UniversityBeijing100084P. R. China
| | - Qiyuan Tian
- School of Biomedical EngineeringTsinghua UniversityBeijing100084P. R. China
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Roy E, Van Rinsveld A, Nedelec P, Richie-Halford A, Rauschecker AM, Sugrue LP, Rokem A, McCandliss BD, Yeatman JD. Differences in educational opportunity predict white matter development. Dev Cogn Neurosci 2024; 67:101386. [PMID: 38676989 DOI: 10.1016/j.dcn.2024.101386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Revised: 02/05/2024] [Accepted: 04/15/2024] [Indexed: 04/29/2024] Open
Abstract
Coarse measures of socioeconomic status, such as parental income or parental education, have been linked to differences in white matter development. However, these measures do not provide insight into specific aspects of an individual's environment and how they relate to brain development. On the other hand, educational intervention studies have shown that changes in an individual's educational context can drive measurable changes in their white matter. These studies, however, rarely consider socioeconomic factors in their results. In the present study, we examined the unique relationship between educational opportunity and white matter development, when controlling other known socioeconomic factors. To explore this question, we leveraged the rich demographic and neuroimaging data available in the ABCD study, as well the unique data-crosswalk between ABCD and the Stanford Education Data Archive (SEDA). We find that educational opportunity is related to accelerated white matter development, even when accounting for other socioeconomic factors, and that this relationship is most pronounced in white matter tracts associated with academic skills. These results suggest that the school a child attends has a measurable relationship with brain development for years to come.
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Affiliation(s)
- Ethan Roy
- Graduate School of Education, Stanford University, Stanford, CA, USA.
| | | | - Pierre Nedelec
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Adam Richie-Halford
- Graduate School of Education, Stanford University, Stanford, CA, USA; Division of Developmental-Behavioral Pediatrics, Stanford University, Stanford, CA, USA
| | - Andreas M Rauschecker
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Leo P Sugrue
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Ariel Rokem
- Department of Psychology and eScience Institute, University of Washington, Seattle, WA, USA
| | | | - Jason D Yeatman
- Graduate School of Education, Stanford University, Stanford, CA, USA; Division of Developmental-Behavioral Pediatrics, Stanford University, Stanford, CA, USA
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Hosoki M, Eidsness MA, Bruckert L, Travis KE, Feldman HM. Associations of behavioral problems with white matter circuits connecting to the frontal lobes in school-aged children born at term and preterm. NEUROIMAGE. REPORTS 2024; 4:100201. [PMID: 39301247 PMCID: PMC11412113 DOI: 10.1016/j.ynirp.2024.100201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 09/22/2024]
Abstract
Introduction This study investigated whether internalizing and externalizing behavioral problems in children were associated with fractional anisotropy of white matter tracts connecting other brain regions to the frontal lobes. We contrasted patterns of association between children born at term (FT) and very preterm (PT: gestational age at birth =< 32 weeks). Methods Parents completed the Child Behavior Checklist/6-18 questionnaire to quantify behavioral problems when their children were age 8 years (N = 36 FT and 37 PT). Diffusion magnetic resonance scans were collected at the same age and analyzed using probabilistic tractography. Multiple linear regressions investigated the strength of association between age-adjusted T-scores of internalizing and externalizing problems and mean fractional anisotropy (mean-FA) of right and left uncinate, arcuate, anterior thalamic radiations, and dorsal cingulate bundle, controlling for birth group and sex. Results Models predicting internalizing T-scores found significant group-by-tract interactions for left and right arcuate and right uncinate. Internalizing scores were negatively associated with mean-FA of left and right arcuate only in FT children (p left AF = 0.01, p right AF = 0.01). Models predicting externalizing T-scores found significant group-by-tract interactions for the left arcuate and right uncinate. Externalizing scores were negatively associated with mean-FA of right uncinate in FT (p right UF = 0.01) and positively associated in PT children (p right UF preterm = 0.01). Other models were not significant. Conclusions In children with a full range of scores on behavioral problems from normal to significantly elevated, internalizing and externalizing behavioral problems were negatively associated with mean-FA of white matter tracts connecting to frontal lobes in FT children; externalizing behavioral problems were positively associated with mean-FA of the right uncinate in PT children. The different associations by birth group suggest that the neurobiology of behavioral problems differs in the two birth groups.
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Affiliation(s)
- Machiko Hosoki
- Division of Developmental-Behavioral Pediatrics, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, USA
| | - Margarita Alethea Eidsness
- Division of Developmental-Behavioral Pediatrics, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, USA
| | - Lisa Bruckert
- Division of Developmental-Behavioral Pediatrics, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, USA
| | - Katherine E Travis
- Division of Developmental-Behavioral Pediatrics, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, USA
| | - Heidi M Feldman
- Division of Developmental-Behavioral Pediatrics, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, USA
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Kleinerova J, Tahedl M, Tan EL, Delaney S, Hengeveld JC, Doherty MA, McLaughlin RL, Hardiman O, Chang KM, Finegan E, Bede P. Supra- and infra-tentorial degeneration patterns in primary lateral sclerosis: a multimodal longitudinal neuroradiology study. J Neurol 2024; 271:3239-3255. [PMID: 38438819 PMCID: PMC11136747 DOI: 10.1007/s00415-024-12261-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 02/14/2024] [Accepted: 02/15/2024] [Indexed: 03/06/2024]
Abstract
BACKGROUND Primary lateral sclerosis (PLS) is traditionally solely associated with progressive upper motor neuron dysfunction manifesting in limb spasticity, gait impairment, bulbar symptoms and pseudobulbar affect. Recent studies have described frontotemporal dysfunction in some patients resulting in cognitive manifestations. Cerebellar pathology is much less well characterised despite sporadic reports of cerebellar disease. METHODS A multi-timepoint, longitudinal neuroimaging study was conducted to characterise the evolution of both intra-cerebellar disease burden and cerebro-cerebellar connectivity. The volumes of deep cerebellar nuclei, cerebellar cortical volumes, cerebro-cerebellar structural and functional connectivity were assessed longitudinally in a cohort of 43 individuals with PLS. RESULTS Cerebello-frontal, -temporal, -parietal, -occipital and cerebello-thalamic structural disconnection was detected at baseline based on radial diffusivity (RD) and cerebello-frontal decoupling was also evident based on fractional anisotropy (FA) alterations. Functional connectivity changes were also detected in cerebello-frontal, parietal and occipital projections. Volume reductions were identified in the vermis, anterior lobe, posterior lobe, and crura. Among the deep cerebellar nuclei, the dorsal dentate was atrophic. Longitudinal follow-up did not capture statistically significant progressive changes. Significant primary motor cortex atrophy and inter-hemispheric transcallosal degeneration were also captured. CONCLUSIONS PLS is not only associated with upper motor neuron dysfunction, but cerebellar cortical volume loss and deep cerebellar nuclear atrophy can also be readily detected. In addition to intra-cerebellar disease burden, cerebro-cerebellar connectivity alterations also take place. Our data add to the evolving evidence of widespread neurodegeneration in PLS beyond the primary motor regions. Cerebellar dysfunction in PLS is likely to exacerbate bulbar, gait and dexterity impairment and contribute to pseudobulbar affect.
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Affiliation(s)
- Jana Kleinerova
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Marlene Tahedl
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Ee Ling Tan
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Siobhan Delaney
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
- Department of Neurology, St James's Hospital, Dublin, Ireland
| | | | - Mark A Doherty
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
| | | | - Orla Hardiman
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Kai Ming Chang
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Eoin Finegan
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Peter Bede
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland.
- Department of Neurology, St James's Hospital, Dublin, Ireland.
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Eichner C, Paquette M, Müller-Axt C, Bock C, Budinger E, Gräßle T, Jäger C, Kirilina E, Lipp I, Morawski M, Rusch H, Wenk P, Weiskopf N, Wittig RM, Crockford C, Friederici AD, Anwander A. Detailed mapping of the complex fiber structure and white matter pathways of the chimpanzee brain. Nat Methods 2024; 21:1122-1130. [PMID: 38831210 PMCID: PMC11166572 DOI: 10.1038/s41592-024-02270-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 03/29/2024] [Indexed: 06/05/2024]
Abstract
Long-standing questions about human brain evolution may only be resolved through comparisons with close living evolutionary relatives, such as chimpanzees. This applies in particular to structural white matter (WM) connectivity, which continuously expanded throughout evolution. However, due to legal restrictions on chimpanzee research, neuroscience research currently relies largely on data with limited detail or on comparisons with evolutionarily distant monkeys. Here, we present a detailed magnetic resonance imaging resource to study structural WM connectivity in the chimpanzee. This open-access resource contains (1) WM reconstructions of a postmortem chimpanzee brain, using the highest-quality diffusion magnetic resonance imaging data yet acquired from great apes; (2) an optimized and validated method for high-quality fiber orientation reconstructions; and (3) major fiber tract segmentations for cross-species morphological comparisons. This dataset enabled us to identify phylogenetically relevant details of the chimpanzee connectome, and we anticipate that it will substantially contribute to understanding human brain evolution.
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Affiliation(s)
- Cornelius Eichner
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Michael Paquette
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Christa Müller-Axt
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Faculty of Psychology, TU Dresden, Dresden, Germany
| | - Christian Bock
- Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany
| | - Eike Budinger
- Leibniz Institute for Neurobiology, Combinatorial NeuroImaging Core Facility, Magdeburg, Germany
- Center for Behavioural Neurosciences, Magdeburg, Germany
| | - Tobias Gräßle
- Ecology and Emergence of Zoonotic Diseases, Helmholtz Institute for One Health, Helmholtz Centre for Infection Research, Greifswald, Germany
| | - Carsten Jäger
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Paul Flechsig Institute - Centre of Neuropathology and Brain Research, Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Evgeniya Kirilina
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany
| | - Ilona Lipp
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Markus Morawski
- Paul Flechsig Institute - Centre of Neuropathology and Brain Research, Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Henriette Rusch
- Paul Flechsig Institute - Centre of Neuropathology and Brain Research, Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Patricia Wenk
- Leibniz Institute for Neurobiology, Combinatorial NeuroImaging Core Facility, Magdeburg, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Roman M Wittig
- Department of Human Behavior, Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Tai Chimpanzee Project, Centre Suisse de Recherches Scientifiques, Abidjan, Côte d'Ivoire
- The Ape Social Mind Lab, Institut des Sciences Cognitives Marc Jeannerod, Lyon, France
| | - Catherine Crockford
- Department of Human Behavior, Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Tai Chimpanzee Project, Centre Suisse de Recherches Scientifiques, Abidjan, Côte d'Ivoire
- The Ape Social Mind Lab, Institut des Sciences Cognitives Marc Jeannerod, Lyon, France
| | - Angela D Friederici
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Alfred Anwander
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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Smolders L, De Baene W, Rutten GJ, van der Hofstad R, Florack L. Can structure predict function at individual level in the human connectome? Brain Struct Funct 2024; 229:1209-1223. [PMID: 38656375 PMCID: PMC11147846 DOI: 10.1007/s00429-024-02796-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 03/25/2024] [Indexed: 04/26/2024]
Abstract
Several studies predicting Functional Connectivity (FC) from Structural Connectivity (SC) at individual level have been published in recent years, each promising increased performance and utility. We investigated three of these studies, analyzing whether the results truly represent a meaningful individual-level mapping from SC to FC. Using data from the Human Connectome Project shared accross the three studies, we constructed a predictor by averaging FC of training data and analyzed its performance in the same way. In each case, we found that group average FC is an equivalent or better predictor of individual FC than the predictive models in terms of raw prediction performance. Furthermore, we showed that additional analyses performed by the authors of the three studies, in which they attempt to show that their predicted FC has value beyond raw prediction performance, could also be reproduced using the group average FC predictor. This makes it unclear whether any of the three methods represent a meaningful individual-level predictive model. We conclude that either the methods are not appropriate for the data, that the sample size is too small, or that the data does not contain sufficient information to learn a mapping from SC to FC. We advise future individual-level studies to explicitly report results in comparison to the performance of the group average, and carefully demonstrate that their predictions contain meaningful individual-level information. Finally, we believe that investigating alternatives for the construction of SC and FC may improve the chances of developing a meaningful individual-level mapping from SC to FC.
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Affiliation(s)
- Lars Smolders
- Eindhoven University of Technology , Department of Mathematics and Computer Science, PO Box 513, Eindhoven, 5600 MB, Netherlands.
- Elisabeth-TweeSteden Hospital, Department of Neurosurgery, Hilvarenbeekseweg 60, Tilburg, 5022 GC, The Netherlands.
| | - Wouter De Baene
- Tilburg University, Department of Cognitive Neuropsychology, Warandelaan 2, Tilburg, 5000 LE, Netherlands
| | - Geert-Jan Rutten
- Elisabeth-TweeSteden Hospital, Department of Neurosurgery, Hilvarenbeekseweg 60, Tilburg, 5022 GC, The Netherlands
| | - Remco van der Hofstad
- Eindhoven University of Technology , Department of Mathematics and Computer Science, PO Box 513, Eindhoven, 5600 MB, Netherlands
| | - Luc Florack
- Eindhoven University of Technology , Department of Mathematics and Computer Science, PO Box 513, Eindhoven, 5600 MB, Netherlands
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Wei YC, Kung YC, Lin CP, Chen CK, Lin C, Tseng RY, Chen YL, Huang WY, Chen PY, Chong ST, Shyu YC, Chang WC, Yeh CH. White matter alterations and their associations with biomarkers and behavior in subjective cognitive decline individuals: a fixel-based analysis. BEHAVIORAL AND BRAIN FUNCTIONS : BBF 2024; 20:12. [PMID: 38778325 PMCID: PMC11110460 DOI: 10.1186/s12993-024-00238-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Accepted: 05/04/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND Subjective cognitive decline (SCD) is an early stage of dementia linked to Alzheimer's disease pathology. White matter changes were found in SCD using diffusion tensor imaging, but there are known limitations in voxel-wise tensor-based methods. Fixel-based analysis (FBA) can help understand changes in white matter fibers and how they relate to neurodegenerative proteins and multidomain behavior data in individuals with SCD. METHODS Healthy adults with normal cognition were recruited in the Northeastern Taiwan Community Medicine Research Cohort in 2018-2022 and divided into SCD and normal control (NC). Participants underwent evaluations to assess cognitive abilities, mental states, physical activity levels, and susceptibility to fatigue. Neurodegenerative proteins were measured using an immunomagnetic reduction technique. Multi-shell diffusion MRI data were collected and analyzed using whole-brain FBA, comparing results between groups and correlating them with multidomain assessments. RESULTS The final enrollment included 33 SCD and 46 NC participants, with no significant differences in age, sex, or education between the groups. SCD had a greater fiber-bundle cross-section than NC (pFWE < 0.05) at bilateral frontal superior longitudinal fasciculus II (SLFII). These white matter changes correlate negatively with plasma Aβ42 level (r = -0.38, p = 0.01) and positively with the AD8 score for subjective cognitive complaints (r = 0.42, p = 0.004) and the Hamilton Anxiety Rating Scale score for the degree of anxiety (Ham-A, r = 0.35, p = 0.019). The dimensional analysis of FBA metrics and blood biomarkers found positive correlations of plasma neurofilament light chain with fiber density at the splenium of corpus callosum (pFWE < 0.05) and with fiber-bundle cross-section at the right thalamus (pFWE < 0.05). Further examination of how SCD grouping interacts between the correlations of FBA metrics and multidomain assessments showed interactions between the fiber density at the corpus callosum with letter-number sequencing cognitive score (pFWE < 0.01) and with fatigue to leisure activities (pFWE < 0.05). CONCLUSION Based on FBA, our investigation suggests white matter structural alterations in SCD. The enlargement of SLFII's fiber cross-section is linked to plasma Aβ42 and neuropsychiatric symptoms, which suggests potential early axonal dystrophy associated with Alzheimer's pathology in SCD. The splenium of the corpus callosum is also a critical region of axonal degeneration and cognitive alteration for SCD.
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Affiliation(s)
- Yi-Chia Wei
- Department of Neurology, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
- Community Medicine Research Center, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, 333, Taiwan
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, 112, Taiwan
| | - Yi-Chia Kung
- Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, 114, Taiwan
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, 112, Taiwan
- Department of Education and Research, Taipei City Hospital, Taipei, Taiwan
| | - Chih-Ken Chen
- Community Medicine Research Center, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, 333, Taiwan
- Department of Psychiatry, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
| | - Chemin Lin
- Community Medicine Research Center, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, 333, Taiwan
- Department of Psychiatry, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
| | - Rung-Yu Tseng
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, 333, Taiwan
| | - Yao-Liang Chen
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, 333, Taiwan
- Department of Radiology, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
| | - Wen-Yi Huang
- Department of Neurology, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, 333, Taiwan
| | - Pin-Yuan Chen
- Community Medicine Research Center, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, 333, Taiwan
- Department of Neurosurgery, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
| | - Shin-Tai Chong
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, 112, Taiwan
| | - Yu-Chiau Shyu
- Community Medicine Research Center, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
- Department of Nursing, Chang Gung University of Science and Technology, Taoyuan, 333, Taiwan
| | - Wei-Chou Chang
- Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, 114, Taiwan
| | - Chun-Hung Yeh
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, 333, Taiwan.
- Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, 333, Taiwan.
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Fuchs C, Dessain Q, Delinte N, Dausort M, Macq B. Sparse Blind Spherical Deconvolution of diffusion weighted MRI. Front Neurosci 2024; 18:1385975. [PMID: 38846718 PMCID: PMC11155299 DOI: 10.3389/fnins.2024.1385975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Accepted: 04/19/2024] [Indexed: 06/09/2024] Open
Abstract
Diffusion-weighted magnetic resonance imaging provides invaluable insights into in-vivo neurological pathways. However, accurate and robust characterization of white matter fibers microstructure remains challenging. Widely used spherical deconvolution algorithms retrieve the fiber Orientation Distribution Function (ODF) by using an estimation of a response function, i.e., the signal arising from individual fascicles within a voxel. In this paper, an algorithm of blind spherical deconvolution is proposed, which only assumes the axial symmetry of the response function instead of its exact knowledge. This algorithm provides a method for estimating the peaks of the ODF in a voxel without any explicit response function, as well as a method for estimating signals associated with the peaks of the ODF, regardless of how those peaks were obtained. The two stages of the algorithm are tested on Monte Carlo simulations, as well as compared to state-of-the-art methods on real in-vivo data for the orientation retrieval task. Although the proposed algorithm was shown to attain lower angular errors than the state-of-the-art constrained spherical deconvolution algorithm on synthetic data, it was outperformed by state-of-the-art spherical deconvolution algorithms on in-vivo data. In conjunction with state-of-the art methods for axon bundles direction estimation, the proposed method showed its potential for the derivation of per-voxel per-direction metrics on synthetic as well as in-vivo data.
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Affiliation(s)
- Clément Fuchs
- Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM), UCLouvain, Louvain-la-Neuve, Belgium
| | - Quentin Dessain
- Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM), UCLouvain, Louvain-la-Neuve, Belgium
- Institute of NeuroScience, UCLouvain, Brussels, Belgium
| | - Nicolas Delinte
- Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM), UCLouvain, Louvain-la-Neuve, Belgium
- Institute of NeuroScience, UCLouvain, Brussels, Belgium
| | - Manon Dausort
- Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM), UCLouvain, Louvain-la-Neuve, Belgium
| | - Benoît Macq
- Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM), UCLouvain, Louvain-la-Neuve, Belgium
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